EDUC 152. Intro to quantitative research in education: Regression analysis
Multivariate regression
1 Introduction
“Bivariate regression” refers to regression models with two variables, a \(Y\) variable (“dependent variable” or “outcome”) and a single \(X\) variable (“independent variable”)
“Multivariate regression” refers to regression models with a \(Y\) variable and two or more \(X\) variables
This lecture introduces multivariate regression, building on concepts we learned from lecture on bivariate regression. In particular, this lecture will focus on:
- Assumptions required to make inferences based on regression analysis
- Using multivariate regression to estimate causal effects
- Interpreting results from multivariate regresssion
- interpreting regression output from R
- interpreting results from publications that use regresion
1.1 Libraries, data, functions
This lecture will utilize data from two sources:
- Tennessee Student Teacher Achievement Ratio (STAR) experiment, which we have worked with before
- The Educational Longitudinal Study (ELS) of 2002
# uncomment below line to remove all objects
#rm(list = ls())
# Libraries
# install packages if you haven't already
#install.packages('tidyverse')
#install.packages('labelled')
#install.packages('haven')
#install.packages('patchwork')
#install.packages("RCurl") #we'll use this to calculate robust standard errors
library(tidyverse)
library(labelled)
library(haven)
#library(RCurl)
#library(patchwork)
##########
########## TENNESSEE STAR DATA
##########
# load star data
load(file = url('https://github.com/anyone-can-cook/educ152/raw/main/data/star/star_panel_data.RData'))
#df_star_panel %>% glimpse()
# create data frame for STAR experiment, keeping only kindergarten
df_stark <- df_star_panel %>%
# keep only kindergarten year
filter(grade ==1) %>%
# keep only observations with non-missing value for reading score
filter(!is.na(read)) %>%
# keep only observations with non-missing values for treatment assignment
filter(!is.na(star)) %>%
# drop observations where treatment status is regular+aide
filter(star !=3) %>%
# keep selected variables
select(id,grade,star,read,gender,ethnicity,lunch,school,degree,experience) %>%
# create a variable "treatment" that equals 1 if student receives treatment (small class) and equals 0 otherwise
mutate(
treatment = if_else(star==2,1,0)
)
df_stark %>% glimpse()
#> Rows: 3,745
#> Columns: 11
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...
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#> $ gender <dbl+lbl> 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 2, 1, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 2, 2, 1, 1, 2, 2, 2, 1, 2, 1, 1, 2, 1, 1, 2, 2, 2, 2, 1, 2, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 1, 1, 2, 2, 2, 2, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 2, 2, 2, 1, 1, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 2, 1, 2, 2, 1, 2, 2, 2, 2, 1, 2, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1, 2, 2, 2, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 2, 1, 2, 1, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 1, 1, 1, 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2, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 2, 2, 1, 2, 1, 2, 2, 1, 2, 2, 2, 2, 1, 2, 1, 2, 1, 2, 1, 1, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 2, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 1, 2, 2, 2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 2, 1, 2, 1, 2, 1, 2, 2, 1, 1, 2, 1, 2, 1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 2, 2, 1, 1, 2, 2, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 1, 2, 1, 2, 2, 2, 1, 1, 2, 2, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 2, 2, 1, 1, 2, 1, 2, 2, 1, ...
#> $ ethnicity <dbl+lbl> 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 2, 3, 1, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 2, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 2, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 2, 2, 1, 1, 2, 1, 2, 1, 2, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 6, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 4, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 1, 2, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 3, 1, 2, 2, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, NA, 2, 1, 2, 1, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 2, 1, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 2, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 1, 2, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 3, 2, 2, 2, 1, 2, 2, 1, 1, 2, 1, 1, 2, 6, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 2, 1, 2, 2, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 2, 2, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 2, 1, 2, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 1, 2, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 2, 2, 1, 1, 2, 1, 2, 2, 1, 1, 2, 2, 1, 1, 2, 1, 1, 5, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 1, 3, 1, 1, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 6, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 3, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 3, 1, 2, 2, 1, 2, 2, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 5, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 2, 1, 2, 2, 1, 2, 2, 1, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 3, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, ...
#> $ lunch <dbl+lbl> 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, 2, 1, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 2, 2, 1, 2, 1, 2, 2, 2, 2, 1, NA, 2, 2, 2, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 1, 1, 2, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 2, 1, 1, 2, 2, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 1, 2, 2, 2, 1, 2, 2, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 2, 2, 1, 1, 2, 2, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 2, 2, 1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, 2, 2, 2, 1, 2, 2, 1, 2, 1, 1, 2, 2, 2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 2, 2, 1, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 2, 2, 1, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1, 2, 2, 2, 1, 2, 1, 2, 1, 1, 1, 2, 2, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 2, 1, 2, 1, 1, 2, 1, 2, 2, 2, 1, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 2, 2, 1, 2, 1, 2, 1, 2, 1, 1, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 1, 2, 1, 1, 1, 2, 2, 2, 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 2, 2, 1, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 1, 1, 2, 1, 2, 2, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 2, 1, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, 2, 1, 2, 2, 1, 1, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 2, 2, 1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 1, 2, 1, 2, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 2, 2, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 2, 2, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 2, 2, 2, 1, 2, 1, 1, 2, 2, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, NA, 1, 2, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 2, 1, 1, 2, 1, 2, 2, 2, 2, 1, 2, 1, 2, 1, 2, 2, 1, 1, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 2, 1, 1, 2, 2, 1, 2, 2, 1, 1, 2, 1, 2, 2, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 1, 2, 1, 2, 2, 2, 1, 2, 1, NA, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 1, 2, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 2, 2, 2, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 2, 1, 2, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 2, 2, 2, 1, 2, 2, 1, 2, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 2, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 2, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 2, 1, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 1, 2, 1, 1, 2, 2, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 2, 2, 1, 2, 1, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 2, 1, 2, 1, 2, 2, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2, 2, 2, 1, 2, 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 2, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 2, 2, 2, 1, 1, 2, 2, 2, 2, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, NA, 1, 1, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 2, 2, 2, 1, 2, 1, 2, 2, 2, 2, 2, 1, 1, 2, 2, 2, 2, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, NA, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 2, 2, 2, 1, 2, 2, 1, 2, 1, 2, 1, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 2, 1, 1, 2, 2, 2, 1, 1, 2, 1, 1, 2, 2, 2, 1, 1, 2, 1, 2, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 2, 2, 1, 2, 2, 1, 1, 2, 2, 2, 1, 1, 1, NA, 2, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 2, 1, 2, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 2, 1, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 2, 1, 1, 2, 1, 2, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 2, 2, 2, 2, 2, 1, 2, 1, 1, 2, 1, 2, 1, 1, 2, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 1, 1, 2, 1, 2, 2, 1, 1, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 1, NA, 2, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 1, 2, 1, 2, 2, 1, 1, 2, 2, 2, 1, 2, 1, 2, 1, 1, 2, 2, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 2, 2, 1, 2, 1, 2, 1, 2, 2, 1, 2, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 2, 2, 2, 1, ...
#> $ school <dbl+lbl> 3, 2, 3, 3, 3, 3, 3, 3, 3, 2, 3, 2, 2, 3, 3, 3, 4, 4, 3, 1, 3, 3, 3, 3, 3, 4, 4, 4, 3, 2, 2, 3, 1, 2, 3, 2, 3, 3, 2, 2, 1, 1, 3, 3, 2, 1, 2, 3, 3, 3, 1, 1, 1, 2, 3, 3, 2, 3, 2, 3, 4, 3, 3, 2, 3, 2, 1, 4, 3, 2, 4, 3, 3, 3, 3, 3, 3, 3, 3, 1, 3, 1, 3, 3, 3, 2, 1, 1, 4, 2, 3, 3, 3, 1, 3, 3, 3, 3, 2, 1, 3, 1, 3, 3, 2, 3, 3, 1, 1, 2, 4, 3, 1, 1, 3, 1, 3, 1, 2, 3, 2, 2, 1, 3, 3, 2, 1, 1, 3, 1, 4, 3, 3, 3, 1, 2, 3, 1, 3, 3, 4, 2, 3, 3, 2, 3, 2, 1, 3, 3, 2, 3, 2, 2, 3, 3, 4, 1, 3, 2, 3, 1, 1, 4, 2, 2, 3, 2, 3, 3, 3, 1, 3, 3, 3, 2, 3, 2, 1, 2, 3, 1, 3, 1, 2, 3, 1, 3, 2, 3, 2, 3, 3, 2, 2, 2, 3, 2, 3, 1, 3, 1, 1, 3, 1, 3, 2, 3, 3, 3, 1, 1, 4, 1, 3, 3, 3, 1, 2, 2, 3, 3, 3, 1, 3, 3, 2, 3, 1, 3, 3, 2, 2, 1, 3, 1, 2, 3, 4, 1, 1, 2, 3, 4, 3, 1, 3, 2, 1, 3, 3, 2, 3, 1, 2, 3, 3, 2, 4, 4, 3, 3, 1, 3, 3, 1, 3, 3, 1, 1, 3, 3, 3, 1, 4, 3, 1, 3, 1, 2, 3, 3, 3, 2, 3, 3, 2, 3, 1, 4, 3, 2, 1, 3, 3, 3, 3, 2, 3, 3, 2, 3, 2, 1, 4, 2, 3, 3, 3, 1, 2, 3, 2, 3, 3, 2, 2, 1, 3, 1, 1, 2, 1, 2, 3, 1, 3, 2, 3, 2, 2, 4, 4, 1, 3, 2, 3, 1, 1, 3, 1, 1, 3, 2, 3, 2, 2, 2, 3, 2, 3, 1, 3, 3, 2, 2, 1, 2, 1, 3, 2, 4, 3, 4, 4, 3, 2, 1, 2, 3, 4, 2, 3, 2, 3, 3, 4, 3, 2, 4, 2, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 2, 3, 2, 3, 1, 3, 3, 3, 4, 1, 3, 2, 3, 3, 3, 1, 3, 2, 2, 3, 2, 2, 1, 3, 2, 1, 3, 2, 2, 3, 3, 3, 4, 4, 3, 3, 2, 3, 3, 3, 3, 3, 2, 3, 1, 1, 3, 1, 4, 1, 2, 4, 2, 3, 1, 1, 2, 2, 3, 1, 3, 3, 4, 4, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 4, 2, 4, 3, 4, 1, 1, 3, 1, 3, 2, 3, 1, 1, 1, 1, 3, 3, 3, 4, 4, 3, 3, 3, 3, 1, 1, 3, 3, 1, 3, 3, 3, 1, 3, 4, 1, 2, 1, 3, 2, 4, 3, 3, 1, 1, 1, 1, 2, 3, 2, 1, 1, 3, 3, 3, 3, 3, 3, 2, 1, 1, 3, 3, 3, 3, 3, 3, 2, 3, 2, 3, 3, 2, 3, 2, 3, 2, 1, 3, 3, 4, 3, 3, 3, 1, 2, 3, 2, 2, 1, 3, 1, 3, 3, 3, 3, 3, 1, 1, 3, 3, 1, 3, 3, 3, 3, 3, 3, 3, 3, 1, 2, 4, 4, 4, 4, 4, 1, 2, 2, 1, 1, 2, 3, 3, 1, 2, 3, 2, 3, 2, 3, 3, 3, 1, 1, 2, 2, 3, 1, 2, 3, 4, 4, 3, 3, 1, 1, 1, 2, 3, 2, 4, 3, 1, 3, 4, 3, 3, 3, 3, 2, 3, 3, 4, 3, 1, 3, 2, 3, 3, 3, 2, 3, 4, 2, 1, 2, 1, 3, 3, 1, 3, 2, 2, 2, 2, 4, 2, 2, 4, 2, 2, 3, 3, 1, 2, 2, 4, 1, 4, 3, 3, 3, 3, 2, 1, 2, 3, 1, 3, 3, 1, 3, 3, 3, 3, 3, 4, 2, 3, 3, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 3, 3, 4, 2, 3, 2, 2, 1, 3, 2, 1, 3, 2, 3, 3, 3, 1, 2, 2, 1, 2, 3, 3, 3, 3, 3, 3, 1, 3, 4, 3, 3, 2, 4, 3, 1, 2, 2, 3, 3, 3, 3, 2, 3, 3, 2, 3, 1, 1, 4, 3, 3, 3, 1, 4, 3, 3, 3, 3, 1, 3, 3, 1, 3, 3, 2, 2, 1, 3, 3, 1, 3, 3, 3, 3, 3, 2, 3, 4, 3, 1, 1, 1, 3, 3, 1, 3, 1, 3, 3, 3, 3, 1, 3, 2, 3, 3, 3, 2, 4, 3, 4, 1, 1, 1, 3, 1, 4, 2, 1, 2, 3, 2, 3, 3, 2, 3, 3, 3, 3, 3, 2, 3, 3, 2, 1, 1, 3, 3, 2, 3, 1, 2, 3, 3, 2, 3, 4, 3, 3, 3, 3, 3, 1, 4, 4, 3, 1, 4, 3, 3, 2, 4, 2, 4, 2, 2, 3, 4, 2, 2, 3, 2, 4, 3, 3, 3, 1, 3, 1, 3, 2, 3, 1, 3, 1, 2, 1, 3, 3, 2, 3, 4, 1, 3, 1, 3, 2, 3, 3, 2, 2, 3, 3, 1, 1, 3, 2, 4, 4, 1, 3, 3, 1, 3, 1, 2, 3, 3, 3, 3, 1, 2, 1, 3, 3, 1, 2, 1, 1, 2, 3, 3, 3, 3, 2, 2, 3, 1, 2, 4, 3, 3, 1, 3, 1, 2, 3, 2, 2, 2, 3, 3, 3, 3, 2, 2, 2, 3, 3, 4, 3, 3, 3, 3, 2, 2, 2, 3, 1, 3, 1, 3, 3, 3, 3, 3, 2, 1, 3, 3, 1, 1, 3, 2, 3, 3, 1, 2, 3, 3, 1, 3, 3, 3, 3, 1, 3, 4, 2, 4, 3, 3, 1, 3, 4, 4, 1, 4, 3, 2, 3, 3, 1, 2, 1, 1, 1, 3, 4, 3, 1, 1, 2, 1, 3, 1, 3, 2, 1, 3, 1, 1, 3, 3, 2, 3, 4, 3, 3, 1, 1, 4, 4, 3, 3, 2, 2, 2, 2, 1, 3, 4, 3, 1, 1, 2, 3, 4, 3, 3, 4, 2, 3, 3, 4, 3, 2, 4, 1, 4, 2, 1, 4, 3, 2, 4, 2, 3, 3, 3, 3, 4, 1, 2, 2, 1, 1, 1, 3, 3, 1, 3, 4, 4, 1, 3, 2, 3, 4, 3, 3, 3, 3, 3, 2, 3, 3, 2, 3, 3, 3, 2, 3, 1, 3, 1, 1, 4, 2, 3, 1, 3, 1, 1, 3, 2, 1, 3, 3, 2, 1, 3, 3, 3, 3, 1, 2, 4, 3, 4, 2, 4, 4, 3, 3, 1, 1, 3, 1, 4, 3, 1, 2, 1, 2, 4, 3, 2, 3, 1, 1, 2, 4, 3, 3, 1, 3, 2, 1, 3, 1, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 2, 3, 4, 3, 1, 2, 3, 3, 4, 3, 3, 3, 3, 3, 3, 2, 2, 3, 3, 3, 4, 3, 3, 3, 1, 3, 3, 1, 2, 2, 3, 1, 4, 3, 2, 1, 3, 1, 3, 3, 3, 2, 3, 3, 1, 3, 3, 1, 3, 1, 3, 3, 1, 1, 3, 2, 3, 1, 2, 2, 3, 3, 2, 2, 1, 3, 1, 3, 2, 1, 3, 1, 3, 3, 3, 3, 3, 1, 3, 4, 3, 3, 1, 1, 3, 3, 3, 3, 4, 3, 2, 2, 2, 3, 3, 3, 1, 3, 2, 2, 3, 3, 4, 3, 3, 3, 1, 3, 2, 1, 3, 4, 2, 3, 3, 4, 2, 3, 3, 1, 3, 1, 3, 2, 1, 2, 3, 1, 2, 1, 3, 3, 2, 3, 1, 1, 3, 2, 2, 2, 2, 3, 3, 2, 3, 1, 1, 3, 1, 4, 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3, 3, 4, 4, 2, 2, 4, 2, 3, 1, 3, 2, 1, 3, 2, 3, 3, 4, 3, 3, 3, 1, 3, 3, 1, 3, 2, 3, 2, 3, 2, 2, 4, 3, 1, 2, 2, 1, 3, 3, 2, 4, 3, 3, 3, 3, 1, 3, 2, 3, 3, 3, 2, 2, 2, 4, 4, 2, 1, 3, 3, 2, 1, 1, 3, 3, 3, 3, 1, 2, 3, 3, 2, 1, 3, 3, 3, 3, 4, 3, 3, 4, 2, 1, 3, 3, 3, 1, 1, 3, 3, 3, 3, 2, 3, 3, 1, 4, 1, 3, 2, 3, 2, 4, 3, 3, 4, 2, 1, 3, 3, 3, 3, 1, 2, 3, 1, 2, 3, 2, 3, 1, 2, 1, 1, 3, 3, 2, 3, 1, 3, 4, 3, 4, 3, 3, 2, 3, 2, 3, 3, 2, 3, 2, 3, 1, 3, 2, 2, 2, 3, 4, 3, 3, 2, 3, 3, 4, 2, 3, 1, 3, 2, 1, 1, 1, 1, 2, 1, 3, 3, 3, 3, 4, 2, 3, 4, 2, 3, 1, 2, 1, 4, 1, 3, 3, 3, 3, 3, 1, 3, 1, 1, 3, 1, 1, 3, 3, 1, 3, 1, 1, 3, 3, 1, 1, 2, 3, 1, 2, 2, 3, 3, 3, 3, 4, 1, 2, 3, 1, 1, 2, 1, 3, 3, 3, 3, 2, 2, 2, 2, 1, 1, 3, 1, 1, 3, 3, 1, 3, 3, 3, 1, 3, 1, 1, 1, 3, 2, 1, 3, 3, 3, 2, 1, 3, 1, 2, 2, 3, 3, 1, 3, 4, 1, 1, 1, 3, 1, 1, 3, 3, 3, 3, 3, 3, 2, 3, 3, 2, 3, 1, 3, 1, 3, 1, 1, 1, 3, 2, 2, 2, 3, 4, 3, 1, 3, 3, 3, 1, 4, 3, 1, 3, 3, 2, 4, 3, 3, 1, 3, 2, 3, 1, 3, 2, 3, 4, 3, 3, 1, 3, 3, 1, 1, 3, 2, 2, 3, 3, 3, 3, 1, 3, 2, 4, 3, 4, 1, 2, 3, 3, 1, 1, 1, 1, 3, 3, 3, 3, 2, 3, 3, 2, 4, 2, 3, 3, 1, 4, 3, 1, 1, 1, 3, 3, 3, 3, 3, 1, 3, 1, 2, 1, 3, 2, 3, 1, 2, 4, 3, 2, 2, 1, 2, 3, 3, 1, 3, 1, 2, 2, 3, 3, 3, 3, 2, 1, 3, 1, 1, 3, 2, 3, 3, 3, 2, 3, 3, 1, 1, 1, 2, 2, 3, 3, 1, 3, 3, 3, 4, 1, 2, 2, 2, 3, 2, 3, 1, 1, 1, 3, 3, 1, 1, 1, 3, 3, 3, 4, 3, 3, 2, 1, 3, 2, 2, 3, 1, 2, 3, 1, 2, 3, 3, 3, 1, 3, 3, 1, 3, 3, 1, 3, 3, 3, 4, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 4, 2, 2, 1, 3, 3, 3, 3, 3, 2, 3, 1, 3, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 1, 2, 3, 1, 3, 3, 2, 3, 1, 3, 4, 1, 4, 2, 3, 2, 4, 3, 3, 3, 3, 2, 3, 3, 3, 2, 4, 1, 1, 2, 3, 1, 3, 2, 3, 3, 1, 4, 1, 3, 4, 1, 4, 1, 3, 3, 2, 2, 3, 2, 1, 3, 1, 2, 3, 3, 1, 1, 2, 1, 3, 2, 2, 3, 3, 3, 3, 4, 3, 1, 1, 3, 4, 1, 3, 1, 2, 1, 2, 2, 4, 2, 1, 3, 3, 3, 3, 3, 3, 4, 3, 2, 2, 1, 4, 3, 3, 3, 3, 1, 3, 1, 3, 1, 3, 3, 4, 3, 3, 3, 4, 4, 1, 4, 3, 2, 2, 3, 1, 3, 2, 2, 2, 4, 3, 3, 4, 2, 3, 3, 3, 3, 2, 3, 1, 1, 3, 2, 4, 2, 3, 2, 3, 3, 1, 3, 3, 4, 2, 2, 1, 2, 3, 2, 2, 3, 3, 4, 3, 3, 3, 4, 1, 1, 3, 1, 3, 2, 2, 3, 1, 1, 3, 1, 2, 3, 3, 3, 1, 1, 1, 3, 4, 3, 2, 4, 4, 2, 3, 4, 3, 3, 3, 1, 3, 1, 2, 2, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 3, 1, 2, 1, 1, 3, 3, 3, 3, 3, 1, 3, 2, 4, 3, 1, 4, 1, 1, 2, 3, 4, 3, 3, 4, 3, 3, 3, 3, 3, 3, 4, 2, 3, 3, 2, 3, 3, 1, 4, 4, 2, 2, 2, 3, 2, 2, 1, 2, 2, 1, 3, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 4, 4, 3, 3, 2, 3, 2, 1, 1, 1, 3, 3, 3, 3, 3, 2, 3, 2, 3, 1, 3, 3, 3, 3, 3, 3, 3, 2, 3, 2, 3, 1, 3, 4, 2, 1, 1, 3, 4, 1, 1, 3, 1, 3, 2, 3, 3, 2, 1, 4, 3, 1, 2, 3, 3, 3, 3, 3, 1, 2, 3, 3, 2, 2, 3, 2, 1, 4, 2, 2, 4, 3, 1, 1, 2, 4, 2, 1, 1, 3, 3, 3, 3, 1, 2, 3, 3, 3, 2, 3, 1, 2, 3, 3, 3, 4, 3, 3, 1, 3, 2, 3, 3, 3, 3, 4, 3, 3, 2, 3, 3, 2, 3, 3, 3, 3, 1, 4, 3, 3, 3, 3, 3, 3, 1, 3, 2, 3, 3, 3, 3, 3, 2, 3, 1, 3, 1, 2, 1, 1, 3, 3, 3, 3, 2, 4, 2, 3, 3, 3, 2, 1, 3, 3, 3, 3, 3, 2, 3, 2, 2, 2, 3, 3, 4, 3, 4, 2, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 1, 2, 4, 3, 3, 3, 1, 3, 3, 1, 3, 2, 2, 3, 3, 3, 3, 1, 1, 2, 1, 4, 3, 2, 3, 3, 4, 3, 3, 4, 4, 1, 1, 2, 1, 3, 1, 3, 2, 2, 3, 1, 4, 3, 3, 3, 3, 1, 3, 3, 4, 3, 2, 3, 3, 3, 3, 1, 3, 1, 1, 2, 3, 4, 2, 1, 1, 2, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 2, 1, 3, 3, 1, 3, 3, 2, 4, 3, 3, 2, 1, 1, 2, 4, 3, 4, 3, 3, 3, 2, 4, 3, 4, 4, 1, 1, 3, 2, 3, 1, 3, 3, 1, 1, 3, 4, 1, 3, 3, 1, 3, 3, 3, 3, 1, 3, 2, 3, 4, 1, 4, 1, 3, 3, 1, 1, 4, 3, 3, 2, 3, 4, 1, 4, 4, 4, 4, 3, 2, 1, 1, 4, 3, 3, 4, 4, 3, 3, 1, 1, 2, 3, 2, 3, 3, 1, 1, 3, 2, 2, 3, 2, 3, 3, 1, 3, 3, 4, 2, 2, 1, 3, 2, 3, 2, 3, 3, 1, 2, 3, 3, 3, 3, 3, 3, 3, 2, 3, 2, 4, 1, 2, 3, 3, 3, 1, 1, 2, 1, 3, 3, 4, 2, 1, 3, 1, 3, 3, 2, 4, 3, 3, 1, 3, 2, 3, 1, 1, 3, 2, 3, 3, 3, 1, 2, 3, 1, 3, 3, 3, 3, 2, 1, 2, 2, 3, 2, 3, 1, 1, 2, 3, 3, 3, 1, 3, 3, 3, 4, 3, 1, 2, 2, 2, 2, 3, 4, 3, 1, 3, 3, 3, 4, 3, 2, 3, 1, 3, 3, 4, 2, 1, 2, 1, 3, 3, 3, 1, 3, 3, 3, 3, 3, 1, 2, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3, 4, 2, 3, 2, 3, 2, 4, 3, 3, 2, 4, 4, 3, 1, 3, 3, 2, 2, 3, 2, 1, 1, 2, 3, 2, 4, 3, 3, 1, 2, 3, 3, 3, 1, 3, 2, 3, 3, 3, 2, 3, 3, 3, 1, 2, 1, 3, 1, 1, 4, 3, 3, 1, 4, 2, 4, 2, 3, 1, 1, 4, 2, 2, 1, 3, 4, 3, 1, 1, 2, 3, 2, 4, 1, 4, 3, 3, 2, 2, 2, 1, 3, 2, 2, 3, 1, 4, 3, 1, 1, 2, 2, 3, 2, 3, 3, 2, 4, 2, 3, 3, 3, 2, 4, 1, 3, 2, 2, 2, 2, 3, 2, 1, 3, 1, 3, 3, 1, 3, 3, 2, 3, 2, 4, 3, 3, 3, 3, 3, 3, 2, 4, 3, 2, 2, 2, 3, 3, 1, 3, 3, 1, 3, 4, 3, 4, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 1, 3, 3, 3, 1, 2, 1, 4, 2, 3, 3, 3, 3, 3, 3, 3, 1, 3, 3, 2, 3, 3, 3, 1, 3, 2, 2, 3, 2, 3, 3, 2, 3, 2, 2, 3, 2, 3, 1, 2, 2, 3, 2, 3, 1, 1, 3, 1, 3, 3, 1, 3, 3, 1, 3, 2, 1, 3, 3, 1, 2, 3, 1, 1, 1, 3, 1, 2, 3, 1, 3, 3, 3, 3, 3, 3, 1, 3, 1, 1, 1, 2, 3, 3, 1, 1, 2, 2, 2, 2, 2, 2, 1, 2, 2, 3, 3, 4, 2, 1, 3, 3, 1, 1, 2, 2, 2, 1, 2, 1, 3, 3, 3, 3, 2, 3, 2, 1, 4, 2, 4, 2, 4, 3, 3, 3, 3, 4, 3, 2, 3, 3, 3, 3, 3, 4, 2, 3, 2, 2, 1, 1, 3, 3, 3, 3, 1, 4, 3, 3, 2, 3, 1, 2, 1, 2, 1, 2, 3, 3, 3, 2, 3, 1, 3, 3, 2, 3, 2, 2, 2, 1, 2, 3, 2, 4, 3, 2, 2, 1, 1, 3, 1, 3, 3, 3, 3, 3, 2, 1, 3, 1, 3, 3, 3, 2, 3, 2, 3, 3, 3, 3, 3, 1, 3, 1, 3, 3, 1, 1, 1, 1, 4, 3, 3, 1, 1, 1, 2, 4, 1, 3, 3, 3, 4, 2, 1, 1, 2, 1, 1, 3, 3, 3, 4, 3, 3, 2, 3, 3, 3, 3, 1, 3, 1, 2, 3, 1, 2, 2, 3, 3, 1, 3, ...
#> $ degree <dbl+lbl> 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 2, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 2, 4, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 4, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 2, 3, 1, 1, 1, 1, 4, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 4, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 4, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1, 4, 2, 2, 2, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 2, 1, 1, 2, 1, 2, 2, 2, 1, 2, 2, 1, 1, 1, 1, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 3, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 3, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 2, 1, 3, 2, 1, 1, 4, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 4, 4, 1, 1, 1, 1, 1, 2, 3, 4, 1, 2, 1, 1, 1, 1, 2, 4, 1, 4, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 2, 1, 2, 1, 2, 4, 1, 2, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 3, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 2, 2, 1, 2, 1, 1, 1, 1, 2, 4, 3, 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 4, 4, 1, 2, 2, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 4, 1, 2, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 3, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 2, 2, 1, 2, 2, 1, 2, 1, 4, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 2, 1, 1, 2, 1, 4, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 2, 3, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 4, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 4, 2, 2, 4, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 4, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 4, 2, 1, 4, 2, 2, 4, 2, 1, 4, 1, 2, 1, 1, 2, 2, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 2, 1, 2, 2, 1, 1, 1, 2, 1, 4, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 2, 1, 1, 2, 2, 2, 2, 1, 1, 2, 1, 2, 2, 1, 2, 2, 1, 4, 2, 2, 1, 2, 1, 1, 3, 2, 2, 2, 4, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 4, 2, 4, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 4, 1, 2, 1, 1, 4, 1, 2, 1, 2, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 4, 2, 1, 3, 1, 2, 1, 2, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 2, 2, 2, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 1, 2, 2, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 1, 2, 2, 1, 1, 3, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 4, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 3, 2, 1, 1, 1, 1, 1, 4, 1, 2, 2, 1, 1, 4, 2, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 2, 1, 2, 4, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 4, 1, 1, 2, 4, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 2, 4, 1, 1, 4, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 4, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, 1, 1, 2, 2, 1, 1, 1, 1, 2, 4, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 4, 1, 2, 1, 2, 2, 1, 1, 2, 2, 1, 4, 2, 2, 2, 1, 1, 1, 1, 1, 1, 3, 2, 2, 1, 1, 1, 2, 1, 1, 2, 4, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 2, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 3, 2, 1, 1, 2, 2, 2, 2, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 4, 2, 4, 4, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 4, 1, 2, 4, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 2, 1, 1, 1, 2, 1, 2, 4, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 4, 1, 2, 1, 2, 2, 1, 1, 2, 2, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 4, 2, 1, 2, 1, 1, 2, 2, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 2, 2, 1, 1, 1, 3, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 4, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 3, 2, 1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 4, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 2, 1, 2, 1, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 4, 1, 1, 1, 2, 1, 2, 1, 2, 2, 1, 2, 1, 1, 2, 1, 1, 1, 4, 1, 2, 1, 1, 2, 1, 1, 1, 1, 3, 1, 2, 4, 1, 1, 3, 2, 2, 1, 2, 2, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 2, 4, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 4, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 2, 4, 1, 1, 1, 2, 1, 4, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 4, 1, 2, 1, 1, 2, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 2, 4, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 4, 1, 1, 2, 1, 1, 4, 1, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 4, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 4, 1, 1, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 2, 2, 3, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 3, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 4, 2, 2, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 4, 2, 3, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 3, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 4, 1, 2, 1, 2, 2, 2, 1, 3, 1, 1, 2, 2, 1, 2, 2, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 4, 1, 1, 1, 1, 1, 2, 1, 1, 4, 1, 2, 1, 1, 1, 1, 2, 4, 2, 1, 1, 1, 1, 1, 1, 1, 3, 1, 2, 1, 4, 3, 1, 1, 1, 2, 1, 2, 2, 2, 1, 2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 1, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 4, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 3, 2, 1, 2, 2, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 4, 1, 2, 1, 2, 4, 2, 1, 2, 1, 2, 4, 1, 1, 3, 1, 1, 1, 1, 1, 2, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 3, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 3, 2, 2, 2, 1, 2, 2, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 2, 1, 4, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 2, 1, 1, 2, 2, 2, 1, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 2, 2, 1, 2, 4, 1, 2, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 3, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 4, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 4, 1, 2, 1, 2, 4, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 4, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 2, 2, 4, 1, 2, 1, 1, 2, 2, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 2, 2, 1, 2, 2, 1, 1, 1, 2, 4, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 4, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 4, 1, 1, 1, 1, 2, 4, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 2, 4, 2, 1, 1, 2, 2, 1, 2, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 4, 1, 1, 1, 2, 1, 1, 1, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 2, 1, 4, 1, 1, 1, 1, 1, 1, 1, 3, 2, 1, 1, 1, 2, 4, 2, 2, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, ...
#> $ experience <int> 7, 21, 16, 5, 8, 3, 11, 10, 13, 0, 6, 13, 1, 8, 13, 13, 14, 8, 13, 0, 8, 15, 8, 10, 4, 7, 17, 12, 4, 0, 18, 4, 12, 14, 13, 14, 5, 5, 1, 5, 2, 2, 11, 13, 5, 0, 4, 5, 8, 2, 11, 14, 13, 3, 15, 20, 11, 20, 6, 11, 12, 6, 12, 18, 2, 11, 1, 17, 0, 13, 17, 20, 4, 15, 6, 10, 4, 16, 8, 6, 15, 10, 15, 8, 10, 3, 6, 6, 1, 13, 13, 9, 8, 6, 11, 8, 19, 8, 18, 3, 12, 5, 6, 8, 10, 8, 2, 11, 0, 14, 0, 7, 7, 0, 21, 0, 12, 12, 0, 1, 5, 3, 1, 2, 10, 14, 2, 1, 4, 11, 1, 0, 0, 3, 15, 3, 13, 3, 10, 11, 12, 11, 8, 16, 15, 10, 1, 9, 15, 8, 4, 4, 16, 13, 4, 9, 13, 9, 4, 12, 11, 1, 2, 11, 13, 14, 6, 11, 12, 6, 4, 9, 1, 10, 12, 8, 12, 15, 1, 20, 6, 9, 5, 0, 4, 14, 12, 2, 8, 6, 3, 15, 17, 14, 15, 4, 3, 11, 7, 10, 12, 9, 6, 1, 3, 1, 0, 8, 6, 11, 15, 10, 5, 9, 11, 5, 13, 24, 13, 7, 8, 5, 4, 9, 17, 8, 11, 15, 2, 8, 4, 0, 4, 12, 4, 3, 21, 5, 3, 12, 15, 7, 0, 4, 13, 2, 2, 4, 10, 17, 6, 24, 6, 2, 18, 8, 2, 12, 5, 5, 4, 8, 0, 13, 6, 9, 27, 19, 7, 3, 14, 1, 10, 6, 6, 9, 11, 16, 2, 15, 12, 10, 2, 15, 16, 12, 13, 8, 9, 0, 11, 3, 11, 3, 5, 20, 5, 1, 6, 0, 12, 12, 8, 14, 3, 10, 1, 2, 2, 1, 0, 4, 12, 16, 16, 3, 15, 12, 6, 0, 0, 1, 5, 20, 6, 24, 12, 1, 8, 13, 3, 14, 17, 24, 11, 11, 13, 14, 7, 4, 2, 21, 6, 16, 2, 12, 0, 1, 12, 0, 13, 3, 3, 1, 16, 13, 5, 12, 12, 8, 24, 14, 12, 11, 14, 1, 15, 1, 18, 11, 6, 12, 10, 7, 6, 12, 0, 19, 3, 5, 18, 8, 8, 12, 8, 8, 10, 10, 15, 6, 0, 6, 15, 20, 3, 11, 8, 10, 2, 5, 5, 14, 22, 11, 10, 20, 5, 9, 14, 16, 21, 18, 6, 9, 13, 0, 2, 8, 13, 11, 8, 8, 4, 4, 11, 15, 5, 5, 13, 11, 8, 5, 20, 3, 6, 15, 5, 4, 1, 13, 7, 7, 3, 11, 10, 0, 10, 17, 10, 15, 1, 16, 6, 13, 12, 4, 4, 11, 8, 0, 16, 10, 6, 3, 5, 11, 22, 9, 3, 15, 13, 13, 13, 6, 13, 8, 0, 8, 4, 15, 2, 9, 3, 1, 2, 13, 12, 6, 7, 13, 13, 0, 11, 3, 13, 1, 12, 8, 2, 8, 11, 12, 19, 7, 6, 0, 11, 8, 11, 5, 13, 11, 9, 10, 6, 2, 15, 11, 10, 14, 6, 6, 6, 5, 3, 8, 14, 8, 3, 1, 4, 4, 13, 21, 2, 17, 6, 1, 12, 5, 13, 20, 8, 13, 21, 13, 11, 8, 13, 13, 10, 4, 5, 12, 20, 13, 18, 3, 7, 8, 8, 10, 6, 6, 5, 1, 0, 9, 13, 2, 2, 11, 19, 8, 12, 8, 8, 6, 13, 8, 13, 5, 6, 14, 11, 11, 15, 8, 11, 9, 6, 10, 12, 19, 8, 10, 13, 12, 8, 8, 5, 0, 19, 10, 21, 6, 0, 11, 2, 3, 11, 4, 12, 4, 12, 3, 11, 2, 14, 8, 5, 8, 2, 0, 8, 11, 15, 10, 4, 8, 18, 15, 13, 0, 10, 3, 4, 11, 2, 4, 13, 8, 13, 5, 0, 12, 5, 1, 6, 8, 1, 10, 0, 3, 12, 0, 13, 14, 0, 14, 15, 14, 2, 13, 15, 21, 22, 21, 8, 8, 13, 12, 12, 11, 0, 2, 22, 10, 3, 4, 12, 3, 11, 11, 15, 6, 6, 3, 17, 0, 1, 14, 12, 9, 12, 1, 0, 10, 6, 11, 8, 0, 17, 16, 4, 5, 14, 0, 12, 3, 6, 8, 3, 6, 10, 12, 6, 20, 12, 15, 3, 5, 10, 1, 12, 12, 6, 13, 8, 8, 6, 13, 13, 22, 11, 11, 11, 8, 2, 15, 4, 8, 4, 11, 4, 13, 2, 20, 7, 6, 3, 6, 0, 12, 20, 8, 1, 4, 4, 6, 6, 13, 6, 8, 16, 8, 13, 9, 12, 11, 9, 8, 11, 5, 5, 3, 13, 5, 8, 22, 12, 13, 6, 1, 3, 11, 19, 13, 9, 10, 2, 6, 11, 6, 4, 3, 27, 20, 13, 10, 11, 0, 13, 10, 3, 3, 11, 8, 6, 6, 5, 0, 5, 13, 2, 8, 10, 8, 6, 2, 4, 3, 6, 6, 3, 16, 17, 17, 1, 6, 4, 10, 20, 4, 21, 11, 14, 1, 16, 2, 8, 4, 13, 8, 10, 6, 12, 7, 5, 12, 2, 21, 16, 2, 0, 5, 4, 14, 13, 8, 5, 13, 15, 15, 8, 12, 5, 8, 12, 6, 12, 13, 12, 8, 11, 27, 12, 11, 2, 7, 6, 1, 2, 11, 6, 21, 11, 12, 9, 13, 8, 5, 10, 15, 3, 13, 6, 1, 10, 6, 24, 1, 12, 8, 0, 4, 6, 6, 24, 13, 8, 4, 16, 12, 6, 4, 24, 4, 8, 11, 21, 1, 9, 6, 11, 1, 20, 9, 5, 14, 12, 10, 20, 1, 5, 8, 0, 5, 14, 4, 12, 14, 13, 1, 11, 17, 12, 12, 22, 11, 10, 15, 8, 4, 13, 20, 6, 8, 11, 13, 8, 13, 6, 11, 1, 3, 14, 13, 13, 6, 13, 5, 11, 20, 2, 12, 4, 22, 9, 8, 11, 22, 10, 19, 11, 12, 4, 16, 8, 24, 19, 7, 3, 13, 12, 9, 1, 12, 13, 6, 8, 3, 9, 24, 10, 6, 3, 1, 6, 6, 2, 6, 5, 13, 1, 1, 8, 12, 11, 9, 6, 7, 1, 11, 6, 12, 6, 11, 10, 16, 14, 9, 5, 13, 0, 8, 5, 2, 13, 14, 18, 18, 13, 9, 10, 0, 2, 2, 2, 4, 1, 5, 5, 10, 7, 13, 13, 13, 13, 1, 12, 21, 3, 12, 3, 7, 21, 12, 8, 11, 15, 2, 12, 16, 2, 11, 11, 5, 12, 6, 9, 3, 4, 8, 9, 13, 13, 4, 5, 11, 24, 8, 7, 15, 3, 13, 12, 16, 8, 1, 19, 10, 6, 17, 8, 10, 8, 9, 10, 5, 6, 14, 18, 11, 0, 13, 13, 10, 9, 24, 12, 0, 3, 10, 6, 3, 0, 8, 10, 6, 10, 6, 5, 11, 12, 8, 8, 4, 8, 10, 0, 12, 2, 6, 10, 6, 3, 10, 11, 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12, 3, 0...
#> $ treatment <dbl> 1, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 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0, 0, 0...
rm(df_star_panel) # comment this line out if you want to keep data frame df_star_panel
##########
########## RUN SCRIPT THAT CREATES USER DEFINED FUNCTIONS
##########
# source(file = url('https://github.com/anyone-can-cook/educ152/raw/main/scripts/user_defined_functions/create_inference_functions.R'))
##########
########## IPEDS
##########
# Load ipeds dataset from course website url
load(file = url('https://github.com/anyone-can-cook/educ152/raw/main/data/ipeds/output_data/panel_data.RData'))
# Create ipeds data frame with fewer variables/observations
df_ipeds_pop <- panel_data %>%
# keep IPEDS tuition data from fall of which year (e.g., fall 2016 is price for programs in 2016-17 academic year)
filter(year == 2016) %>%
# which universities to keep:
# 2015 carnegie classification: keep research universities (15,16,17) and master's universities (18,19,20)
filter(c15basic %in% c(15,16,17,18,19,20)) %>%
# which variables to keep
select(instnm,unitid,opeid6,opeid,control,c15basic,stabbr,city,zip,locale,obereg, # basic institutional characteristics
tuition6,fee6,tuition7,fee7, # avg tuition and fees for full-time grad, in-state and out-of-state
isprof3,ispfee3,osprof3,ospfee3, # avg tuition and fees for MD, in-state and out-of-state
isprof9,ispfee9,osprof9,ospfee9, # avg tuition and fees for Law, in-state and out-of-state
chg4ay3,chg7ay3,chg8ay3) %>% # [undergraduate] books+supplies; off-campus (not with family) room and board; off-campus (not with family) other expenses
# rename variables; syntax <new_name> = <old_name>
rename(region = obereg, # revion
tuit_grad_res = tuition6, fee_grad_res = fee6, tuit_grad_nres = tuition7, fee_grad_nres = fee7, # grad
tuit_md_res = isprof3, fee_md_res = ispfee3, tuit_md_nres = osprof3, fee_md_nres = ospfee3, # md
tuit_law_res = isprof9, fee_law_res = ispfee9, tuit_law_nres = osprof9, fee_law_nres = ospfee9, # law
books_supplies = chg4ay3, roomboard_off = chg7ay3, oth_expense_off = chg8ay3) %>% # [undergraduate] expenses
# create measures of tuition+fees
mutate(
tuitfee_grad_res = tuit_grad_res + fee_grad_res, # graduate, state resident
tuitfee_grad_nres = tuit_grad_nres + fee_grad_nres, # graduate, non-resident
tuitfee_md_res = tuit_md_res + fee_md_res, # MD, state resident
tuitfee_md_nres = tuit_md_nres + fee_md_nres, # MD, non-resident
tuitfee_law_res = tuit_law_res + fee_law_res, # Law, state resident
tuitfee_law_nres = tuit_law_nres + fee_law_nres) %>% # Law, non-resident
# create measures of cost-of-attendance (COA) as the sum of tuition, fees, book, living expenses
mutate(
coa_grad_res = tuit_grad_res + fee_grad_res + books_supplies + roomboard_off + oth_expense_off, # graduate, state resident
coa_grad_nres = tuit_grad_nres + fee_grad_nres + books_supplies + roomboard_off + oth_expense_off, # graduate, non-resident
coa_md_res = tuit_md_res + fee_md_res + books_supplies + roomboard_off + oth_expense_off, # MD, state resident
coa_md_nres = tuit_md_nres + fee_md_nres + books_supplies + roomboard_off + oth_expense_off, # MD, non-resident
coa_law_res = tuit_law_res + fee_law_res + books_supplies + roomboard_off + oth_expense_off, # Law, state resident
coa_law_nres = tuit_law_nres + fee_law_nres + books_supplies + roomboard_off + oth_expense_off) # %>% # Law, non-resident
# [COMMENTED THIS OUT] keep only observations that have non-missing values for the variable coa_grad_res
# this does cause us to lose some interesting universities, but doing this will eliminate some needless complications with respect to learning core concepts about statistical inference
#filter(!is.na(coa_grad_res))
# Add variable labels to the tuit+fees variables and coa variables
# tuition + fees variables
var_label(df_ipeds_pop[['tuitfee_grad_res']]) <- 'graduate, full-time, resident; avg tuition + required fees'
var_label(df_ipeds_pop[['tuitfee_grad_nres']]) <- 'graduate, full-time, non-resident; avg tuition + required fees'
var_label(df_ipeds_pop[['tuitfee_md_res']]) <- 'MD, full-time, state resident; avg tuition + required fees'
var_label(df_ipeds_pop[['tuitfee_md_nres']]) <- 'MD, full-time, non-resident; avg tuition + required fees'
var_label(df_ipeds_pop[['tuitfee_law_res']]) <- 'Law, full-time, state resident; avg tuition + required fees'
var_label(df_ipeds_pop[['tuitfee_law_nres']]) <- 'Law, full-time, non-resident; avg tuition + required fees'
# COA variables
var_label(df_ipeds_pop[['coa_grad_res']]) <- 'graduate, full-time, state resident COA; == tuition + fees + (ug) books/supplies + (ug) off-campus room and board + (ug) off-campus other expenses'
var_label(df_ipeds_pop[['coa_grad_nres']]) <- 'graduate, full-time, non-resident COA; == tuition + fees + (ug) books/supplies + (ug) off-campus room and board + (ug) off-campus other expenses'
var_label(df_ipeds_pop[['coa_md_res']]) <- 'MD, full-time, state resident COA; == tuition + fees + (ug) books/supplies + (ug) off-campus room and board + (ug) off-campus other expenses'
var_label(df_ipeds_pop[['coa_md_nres']]) <- 'MD, full-time, non-resident COA; == tuition + fees + (ug) books/supplies + (ug) off-campus room and board + (ug) off-campus other expenses'
var_label(df_ipeds_pop[['coa_law_res']]) <- 'Law, full-time, state resident COA; == tuition + fees + (ug) books/supplies + (ug) off-campus room and board + (ug) off-campus other expenses'
var_label(df_ipeds_pop[['coa_law_nres']]) <- 'Law, full-time, non-resident COA; == tuition + fees + (ug) books/supplies + (ug) off-campus room and board + (ug) off-campus other expenses'
#df_ipeds_pop %>% glimpse()
rm(panel_data) # comment this line out if you want to keep data frame panel_data
##########
########## SCORECARD DATA ON DEBT AND EARNINGS
##########
# load scorecard dataset from course website url
load(file = url('https://github.com/anyone-can-cook/educ152/raw/main/data/college_scorecard/output_data/df_debt_earn_panel_labelled.RData'))
df_scorecard <- df_debt_earn_panel_labelled %>%
# keep most recent year of data
filter(field_ay == '2017-18') %>%
# keep master's degrees
filter(credlev == 5) %>%
# carnegie categories to keep: 15 = Doctoral Universities: Very High Research Activity; 16 = Doctoral Universities: High Research Activity
# note: variable ccbasic from scorecard data is 2015 carnegie classification
filter(ccbasic %in% c(15,16,17,18,19,20)) %>%
# drop "parent plus" loan variables and other vars we won't use in this lecture
select(-contains('_pp'),-contains('_any'),-field_ay,-st_fips,-zip,-longitude,-latitude,-locale2,-highdeg,-accredagency,-relaffil,-hbcu,-annhi,-tribal,-aanapii,-hsi,-nanti,-main,-numbranch,-control) %>%
# create variable for broad field of degree (e.g., education, business)
mutate(cipdig2 = str_sub(string = cipcode, start = 1, end = 2)) %>%
# shorten variable cipdesc to make it more suitable for printing
mutate(cipdesc = str_sub(string = cipdesc, start = 1, end = 50)) %>%
# re-order variables
relocate(opeid6,unitid,instnm,ccbasic,stabbr,city,cipdig2)
#df_scorecard %>% glimpse()
# For debt and earnings variables, convert from character to numeric variables (which replaces "PrivacySuppressed" values with NA values)
df_scorecard <- df_scorecard %>%
mutate(
debt_all_stgp_eval_n = as.numeric(debt_all_stgp_eval_n),
debt_all_stgp_eval_mean = as.numeric(debt_all_stgp_eval_mean),
debt_all_stgp_eval_mdn = as.numeric(debt_all_stgp_eval_mdn),
debt_all_stgp_eval_mdn10yrpay = as.numeric(debt_all_stgp_eval_mdn10yrpay),
earn_count_wne_hi_1yr = as.numeric(earn_count_wne_hi_1yr),
earn_mdn_hi_1yr = as.numeric(earn_mdn_hi_1yr),
earn_count_wne_hi_2yr = as.numeric(earn_count_wne_hi_2yr),
earn_mdn_hi_2yr = as.numeric(earn_mdn_hi_2yr),
ipedscount1 = as.numeric(ipedscount1),
ipedscount2 = as.numeric(ipedscount2)
)
# add variable label to variable cipdig2
attr(df_scorecard[['cipdig2']], which = 'label') <- 'broad degree field code = 2-digit classification of instructional programs (CIP) degree code'
# add variable label attribute back to debt and earnings variables
for(v in c('debt_all_stgp_eval_n','debt_all_stgp_eval_mean','debt_all_stgp_eval_mdn','debt_all_stgp_eval_mdn10yrpay','earn_count_wne_hi_1yr','earn_mdn_hi_1yr','earn_count_wne_hi_2yr','earn_mdn_hi_2yr','cipdesc','ipedscount1','ipedscount2')) {
#writeLines(str_c('object v=', v))
#writeLines(attr(df_debt_earn_panel_labelled[[v]], which = 'label'))
attr(df_scorecard[[v]], which = 'label') <- attr(df_debt_earn_panel_labelled[[v]], which = 'label')
}
#df_scorecard %>% glimpse()
rm(df_debt_earn_panel_labelled) # comment this line out if you want to keep data frame df_debt_earn_panel_labelled
#earn_mdn_hi_2yr
##########
########## LEFT JOIN SCORECARD AND IPEDS DATA
##########
# investigate data structure
# df_scorecard; these vars uniquely identify observations
df_scorecard %>% group_by(opeid6,cipcode) %>% summarise(n_per_key=n()) %>% ungroup() %>% count(n_per_key)
#> # A tibble: 1 x 2
#> n_per_key n
#> <int> <int>
#> 1 1 28057
# df_ipeds_pop: these vars uniquely identify observations
df_ipeds_pop %>% group_by(unitid) %>% summarise(n_per_key=n()) %>% ungroup() %>% count(n_per_key)
#> # A tibble: 1 x 2
#> n_per_key n
#> <int> <int>
#> 1 1 1091
# join
# start with df_ipeds_pop, keep selected variables; then do do a right_join (i.e., keep obs in y table)
df_score_ipeds <- df_ipeds_pop %>%
select(-instnm,-opeid6,-opeid,-c15basic,-region,-locale,-city,-stabbr,-zip) %>% mutate(one=1) %>%
right_join(y=df_scorecard, by = 'unitid')
#df_score_ipeds %>% glimpse()
# 52 unitids from scorecard that don't have a match in ipeds
# could be due to differences in year; decision: drop thiese
df_score_ipeds %>% filter(is.na(one)) %>% count(unitid) # 52 unitids from scorecard data with missing IPEDS data
#> # A tibble: 52 x 2
#> unitid n
#> <dbl> <int>
#> 1 108232 21
#> 2 127556 5
#> 3 140872 7
#> 4 140988 3
#> 5 150941 6
#> 6 151290 4
#> 7 152381 3
#> 8 152567 6
#> 9 153001 8
#> 10 153126 3
#> # ... with 42 more rows
df_score_ipeds %>% filter(is.na(one)) %>% count(instnm) # 52 unitids from scorecard data with missing IPEDS data
#> # A tibble: 52 x 2
#> instnm n
#> <chr> <int>
#> 1 Academy of Art University 21
#> 2 Augustana University 4
#> 3 Baker College 12
#> 4 Buena Vista University 8
#> 5 Calvin University 7
#> 6 Cedar Crest College 9
#> 7 Cedarville University 4
#> 8 Clarke University 3
#> 9 Coker University 3
#> 10 Colorado Mesa University 5
#> # ... with 42 more rows
df_score_ipeds <- df_score_ipeds %>%
# drop unitids from scorecard that don't merge to ipeds data (on tuition)
filter(!is.na(one)) %>%
# drop observations that don't have mean debt data
filter(!is.na(debt_all_stgp_eval_mean)) %>%
# drop for-profits
filter(control !=3) %>%
# drop tuition/coa vars for law and md
select(-one,-contains('law'),-contains('md_')) %>%
# create measure of urbanization from locale
mutate(
urban = case_when(
locale %in% c(11) ~ 1, # city
locale %in% c(12,13) ~ 2, # city
locale %in% c(21,22,23) ~ 3, # suburb
locale %in% c(31,32,33,41,42,43) ~ 4 # town/rural
)
) %>%
# create value labels for level of urbanization
set_value_labels(
urban = c(
'large city (250k+)' = 1,
'med/small city' = 2,
'suburb' = 3,
'town/rural' = 4
)
) %>%
# change variable order
relocate(opeid6,unitid,instnm,control,ccbasic,stabbr,region,city,locale,urban,cipdig2,cipcode,cipdesc,credlev,creddesc,
contains('ipeds'),starts_with('debt'),starts_with('earn'))
# create variable label
var_label(df_score_ipeds[['urban']]) <- 'four-category variable of level of urbanization (large city, small/med city, suburb, town/rural) created from locale'
# %>% count(urban, locale) # crosscheck
df_score_ipeds %>% glimpse()
#> Rows: 9,444
#> Columns: 36
#> $ opeid6 <chr> "001002", "001002", "001002", "001002", "001002", "001002", "001002", "001002", "001002", "001002", "001002", "001002", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "001052", "025034", "025034", "001055", "001055", "001055", "001055", "001005", "001005", "001005", "001005", "001005", "001051", "001051", "001051", "001051", "001051", "001051", "001051", "001051", "001051", "001051", "001051", "001051", "001051", "001051", "001051", "001051", "001051", "001051", "001051", "001051", "008310", "008310", "008310", "008310", "008310", "008310", "008310", "008310", "008310", "008310", "008310", "001009", "001009", "001009", "001009", "001009", "001009", "001009", "001009", "001009", "001009", "001009", "001009", "001009", "001009", "001009", "001009", "001009", "001003", "001003", "001003", "001003", "001020", "001020", "001020", "001020", "001020", "001020", "001020", "001020", "001020", "001020", "001020", "001020", "001020", "001020", "001024", "001024", "001024", "001024", "001024", "001024", "001004", "001004", "001004", "001004", "001016", "001016", "001016", "001016", "001016", "001016", "001036", "001036", "001036", "001036", "001036", "001036", "001036", "001036", "001036", "001036", "001057", "001057", "001057", "001057", "001057", "001057", "001057", "001057", "001057", "001057", "001057", "001057", "001057", "001047", "001047", "001047", "001047", "001047", "001047", "001047", "001047", "001047", "001047", "001047", "001047", "001047", "001047", "001050", "011462", "011462", "011462", "011462", "011462", "011462", "001063", "001063", "001065", "001065", "001065", "001065", "001061", "001061", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001081", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001083", "001082", "001082", "001082", "001082", "001082", "001082", "001082", "001082", "001082", "001082", "001082", "001082", "001082", "001082", "001082", "001082", "001082", "020653", "001101", "001101", "001101", "001101", "001101", "001101", "001101", "001101", "001101", "001108", "001108", "001108", "001108", "001108", "001108", "001108", "001108", "001108", "001108", "001108", "001108", "001108", "001108", "001090", "001090", "001090", "001090", "001090", "001090", "001090", "001090", "001090", "001090", "001090", "001090", "001090", "001090", "001090", "001090", "001089", "001089", "001089", "001089", "001089", "001089", "001089", "001089", "001089", "001085", "001085", "001092", "001092", "001092", "001092", "001092", "001092", "001092", "001092", "001092", "001092", "001092", "001092", "001092", "001092", "001092", "001097", "001097", "001097", "001097", "001097", "001097", "001097", "001097", "001097", "001098", "001098", "001098", "001098", "001098", "001100", "001100", "001107", "001107", "001107", "001107", "001107", "001117", "001117", "001117", "001117", "001117", "001117", "001117", "001117", "001117", "001117", "001117", "001117", "001117", "001117", "001117", "001117", "001122", "001122", "001122", "001122", "001122", "001122", "001122", "001122", "001122", "001122", "001122", "012154", "012154", "001125", "001125", "001125", "001125", "001125", "001125", "001125", "001125", "001125", "001125", "001125", "001125", "001125", "001125", "001133", "001133", "001133", "001133", "001133", "001133", "001133", "001133", "001133", "001143", "001143", "001143", "001143", "001143", "001143", "001143", "001143", "001143", "001143", "001143", "001143", "001143", "001143", "001143", "007993", "007993", "007993", "007993", "007993", "007993", "001157", "001157", "001157", "001157", "001142", "001142", "001142", "001142", "001142", "001142", "001142", "001142", "001142", "001142", "001142", "001142", "001142", "001142", "001142", "001144", "001144", "001144", "001144", "001144", "001144", "001144", "001144", "001144", "001146", "001146", "001146", "001146", "001146", "001146", "001141", "001141", "001141", "001141", "001141", "001141", "001141", "001141", "001141", "001141", "001141", "001147", "001147", "001147", "001147", "001147", "001147", "001147", "001147", "001147", "001147", "001147", "001147", "001147", "001147", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001137", "001138", "001138", "001138", "001138", "001138", "001138", "001138", "001138", "001138", "001138", "001138", "001138", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001139", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001140", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001153", "001150", "001150", "001150", "001150", "001150", "001150", "001150", "001150", "001150", "001150", "001150", "001150", "001150", "001150", "001150", "001150", "001150", "001150", "001150", "001150", "001312", "001312", "001312", "001312", "001313", "001313", "001313", "001313", "001313", "001313", "001313", "001313", "001313", "001313", "001314", "001314", "001314", "001314", "001314", "001314", "001314", "001314", "001314", "001314", "001314", "001314", "001314", "001315", "001315", "001315", "001315", "001315", "001315", "001315", "001315", "001315", "001315", "001315", "001315", "001315", "001315", "001315", "001315", "001315", "001315", "001315", "001316", "001316", "001316", "001316", "001317", "001317", "001317", "001317", "001317", "001317", "001317", "001317", "001317", "001317", "001317", "001317", "001317", "001317", "001320", "001321", "001321", "001164", "001164", "001164", "001164", "001164", "001164", "001164", "001164", "020705", "020705", "020705", "020705", "020705", "020705", "020705", "001169", "001169", "001169", "001169", "001169", "001169", "001169", "001169", "001169", "001196", "001196", "001196", "001196", "001196", "001196", "020961", "001253", "001253", "001253", "001253", "001253", "001253", "001253", "001253", "001253", "001205", "001205", "001205", "001205", "001205", "001205", "001205", "001205", "001205", "001183", "001183", "001183", "001183", "001149", "001149", "001149", "001149", "001149", "001149", "001149", "001149", "004484", "004484", "004484", "001216", "001216", "001216", "001216", "001216", "001216", "001216", "001216", "001215", "001215", "001215", "001220", "001220", "011649", "011649", "011649", "011649", "011649", "011649", "011649", "011649", "011649", "011649", "011649", "011649", "011649", "011649", "011649", "011649", "001238", "001238", "001238", "001238", "001238", "001238", "001238", "001243", "001243", "001243", "001243", "001243", "001243", "001243", "001243", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "011460", "001179", "001179", "001179", "001179", "001179", "001252", "001252", "001252", "001252", "001329", "001329", "001329", "001329", "001329", "001329", "001329", "010149", "010149", "010149", "010149", "010149", "010149", "010149", "010149", "010149", "001262", "001262", "001262", "001262", "001262", "001322", "001322", "001322", "001322", "001322", "001322", "001322", "001322", "001151", "001151", 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#> $ unitid <dbl> 100654, 100654, 100654, 100654, 100654, 100654, 100654, 100654, 100654, 100654, 100654, 100654, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100663, 100690, 100690, 100706, 100706, 100706, 100706, 100724, 100724, 100724, 100724, 100724, 100751, 100751, 100751, 100751, 100751, 100751, 100751, 100751, 100751, 100751, 100751, 100751, 100751, 100751, 100751, 100751, 100751, 100751, 100751, 100751, 100830, 100830, 100830, 100830, 100830, 100830, 100830, 100830, 100830, 100830, 100830, 100858, 100858, 100858, 100858, 100858, 100858, 100858, 100858, 100858, 100858, 100858, 100858, 100858, 100858, 100858, 100858, 100858, 101189, 101189, 101189, 101189, 101480, 101480, 101480, 101480, 101480, 101480, 101480, 101480, 101480, 101480, 101480, 101480, 101480, 101480, 101587, 101587, 101587, 101587, 101587, 101587, 101709, 101709, 101709, 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110608, 110608, 110608, 110608, 110608, 110608, 110608, 110617, 110617, 110617, 110617, 110617, 110617, 110617, 110617, 110617, 110617, 110617, 110617, 110617, 110617, 110617, 110617, 110617, 110617, 110617, 110617, 110635, 110635, 110635, 110635, 110644, 110644, 110644, 110644, 110644, 110644, 110644, 110644, 110644, 110644, 110653, 110653, 110653, 110653, 110653, 110653, 110653, 110653, 110653, 110653, 110653, 110653, 110653, 110662, 110662, 110662, 110662, 110662, 110662, 110662, 110662, 110662, 110662, 110662, 110662, 110662, 110662, 110662, 110662, 110662, 110662, 110662, 110671, 110671, 110671, 110671, 110680, 110680, 110680, 110680, 110680, 110680, 110680, 110680, 110680, 110680, 110680, 110680, 110680, 110680, 110705, 110714, 110714, 111948, 111948, 111948, 111948, 111948, 111948, 111948, 111948, 112075, 112075, 112075, 112075, 112075, 112075, 112075, 112251, 112251, 112251, 112251, 112251, 112251, 112251, 112251, 112251, 113698, 113698, 113698, 113698, 113698, 113698, 114549, 114813, 114813, 114813, 114813, 114813, 114813, 114813, 114813, 114813, 115083, 115083, 115083, 115083, 115083, 115083, 115083, 115083, 115083, 115728, 115728, 115728, 115728, 115755, 115755, 115755, 115755, 115755, 115755, 115755, 115755, 116712, 116712, 116712, 117140, 117140, 117140, 117140, 117140, 117140, 117140, 117140, 117627, 117627, 117627, 117751, 117751, 117946, 117946, 117946, 117946, 117946, 117946, 117946, 117946, 117946, 117946, 117946, 117946, 117946, 117946, 117946, 117946, 118888, 118888, 118888, 118888, 118888, 118888, 118888, 119173, 119173, 119173, 119173, 119173, 119173, 119173, 119173, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 119605, 120184, 120184, 120184, 120184, 120184, 120537, 120537, 120537, 120537, 120883, 120883, 120883, 120883, 120883, 120883, 120883, 121150, 121150, 121150, 121150, 121150, 121150, 121150, 121150, 121150, 121309, 121309, 121309, 121309, 121309, 121691, 121691, 121691, 121691, 121691, 121691, 121691, 121691, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122409, 122436, 122436, 122436, 122436, 122436, 122436, 122436, 122436, 122436, 122436, 122436, 122436, 122436, 122436, 122436, 122436, 122436, 122436, 122597, 122597, 122597, 122597, 122597, 122597, 122597, 122597, 122597, 122597, 122597, 122597, 122597, 122597, 122597, 122597, 122597, 122597, 122597, 122597, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122612, 122755, 122755, 122755, 122755, 122755, 122755, 122755, 122755, 122755, 122755, 122755, 122755, 122931, 122931, 122931, 122931, 122931, 122931, 122931, 123457, 123554, 123554, 123554, 123554, 123554, 123554, 123554, 123554, 123554, 123572, 123572, 123572, 123572, 123572, 123572, 123651, 123651, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 123961, 125897, 125897, 126182, 126182, 126182, 126182, 126182, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126562, 126580, 126580, 126580, 126580, 126580, 126580, 126580, 126580, 126580, 126580, 126580, 126614, 126614, 126614, 126614, 126614, 126614, 126614, 126614, 126614, 126614, 126614, 126614, 126614, 126614, 126614, 126614, 126669, 126669, 126669, 126669, 126775, 126775, 126775, 126775, 126775, 126775, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 126818, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127060, 127565, 127565, 127565, 127653, 127653, 127653, 127741, 127741, 127741, 127741, 127741, 127741, 127741, 127741, 127741, 127741, 127741, 127741, 127741, 127741, 127918, 127918, 127918, 127918, 127918, 127918, 127918, 127918, 127918, 127918, 127918, 127918, 128106, 128106, 128106, 128391, 12839...
#> $ instnm <chr> "Alabama A & M University", "Alabama A & M University", "Alabama A & M University", "Alabama A & M University", "Alabama A & M University", "Alabama A & M University", "Alabama A & M University", "Alabama A & M University", "Alabama A & M University", "Alabama A & M University", "Alabama A & M University", "Alabama A & M University", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "University of Alabama at Birmingham", "Amridge University", "Amridge University", "University of Alabama in Huntsville", "University of Alabama in Huntsville", "University of Alabama in Huntsville", "University of Alabama in Huntsville", "Alabama State University", "Alabama State University", "Alabama State University", "Alabama State University", "Alabama State University", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "The University of Alabama", "Auburn University at Montgomery", "Auburn University at Montgomery", "Auburn University at Montgomery", "Auburn University at Montgomery", "Auburn University at Montgomery", "Auburn University at Montgomery", "Auburn University at Montgomery", "Auburn University at Montgomery", "Auburn University at Montgomery", "Auburn University at Montgomery", "Auburn University at Montgomery", "Auburn University", "Auburn University", "Auburn University", "Auburn University", "Auburn University", "Auburn University", "Auburn University", "Auburn University", "Auburn University", "Auburn University", "Auburn University", "Auburn University", "Auburn University", "Auburn University", "Auburn University", "Auburn University", "Auburn University", "Faulkner University", "Faulkner University", "Faulkner University", "Faulkner University", "Jacksonville State University", "Jacksonville State University", "Jacksonville State University", "Jacksonville State University", "Jacksonville State University", "Jacksonville State University", "Jacksonville State University", "Jacksonville State University", "Jacksonville State University", "Jacksonville State University", "Jacksonville State University", "Jacksonville State University", "Jacksonville State University", "Jacksonville State University", "University of West Alabama", "University of West Alabama", "University of West Alabama", "University of West Alabama", "University of West Alabama", "University of West Alabama", "University of Montevallo", "University of Montevallo", "University of Montevallo", "University of Montevallo", "University of North Alabama", "University of North Alabama", "University of North Alabama", "University of North Alabama", "University of North Alabama", "University of North Alabama", "Samford University", "Samford University", "Samford University", "Samford University", "Samford University", "Samford University", "Samford University", "Samford University", "Samford University", "Samford University", "University of South Alabama", "University of South Alabama", "University of South Alabama", "University of South Alabama", "University of South Alabama", "University of South Alabama", "University of South Alabama", "University of South Alabama", "University of South Alabama", "University of South Alabama", "University of South Alabama", "University of South Alabama", "University of South Alabama", "Troy University", "Troy University", "Troy University", "Troy University", "Troy University", "Troy University", "Troy University", "Troy University", "Troy University", "Troy University", "Troy University", "Troy University", "Troy University", "Troy University", "Tuskegee University", "University of Alaska Anchorage", "University of Alaska Anchorage", "University of Alaska Anchorage", "University of Alaska Anchorage", "University of Alaska Anchorage", "University of Alaska Anchorage", "University of Alaska Fairbanks", "University of Alaska Fairbanks", "University of Alaska Southeast", "University of Alaska Southeast", "University of Alaska Southeast", "University of Alaska Southeast", "Alaska Pacific University", "Alaska Pacific University", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "Arizona State University-Tempe", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "University of Arizona", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Northern Arizona University", "Prescott College", "University of Arkansas at Little Rock", "University of Arkansas at Little Rock", "University of Arkansas at Little Rock", "University of Arkansas at Little Rock", "University of Arkansas at Little Rock", "University of Arkansas at Little Rock", "University of Arkansas at Little Rock", "University of Arkansas at Little Rock", "University of Arkansas at Little Rock", "University of Arkansas", "University of Arkansas", "University of Arkansas", "University of Arkansas", "University of Arkansas", "University of Arkansas", "University of Arkansas", "University of Arkansas", "University of Arkansas", "University of Arkansas", "University of Arkansas", "University of Arkansas", "University of Arkansas", "University of Arkansas", "Arkansas State University-Main Campus", "Arkansas State University-Main Campus", "Arkansas State University-Main Campus", "Arkansas State University-Main Campus", "Arkansas State University-Main Campus", "Arkansas State University-Main Campus", "Arkansas State University-Main Campus", "Arkansas State University-Main Campus", "Arkansas State University-Main Campus", "Arkansas State University-Main Campus", "Arkansas State University-Main Campus", "Arkansas State University-Main Campus...
#> $ control <dbl+lbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 17, 17, 17, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 19, 19, 19, 19, 19, 19, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 19, 19, 19, 19, 19, 19, 19, 19, 16, 16, 16, 16, 16, 16, 20, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 19, 19, 19, 19, 19, 18, 18, 18, 18, 18, 18, 18, 18, 18, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 19, 19, 19, 19, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 19, 19, 19, 19, 19, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 18, 18, 18, 18, 18, 18, 18, 20, 20, 20, 19, 19, 19, 19, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 18, 18, 18, 18, 18, 17, 17, 17, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 18, 18, 18, 18, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 18, 18, 18, 18, 18, 18, 18, 18, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 18, 18, 18, 18, 18, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 19, 19, 19, 19, 19, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 17, 17, 17, 17, 17, 17, 17, 17, 17, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 1...
#> $ stabbr <chr> "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AK", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AZ", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DE", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "DC", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL...
#> $ region <dbl+lbl> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 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#> $ city <chr> "Normal", "Normal", "Normal", "Normal", "Normal", "Normal", "Normal", "Normal", "Normal", "Normal", "Normal", "Normal", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Montgomery", "Montgomery", "Huntsville", "Huntsville", "Huntsville", "Huntsville", "Montgomery", "Montgomery", "Montgomery", "Montgomery", "Montgomery", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Tuscaloosa", "Montgomery", "Montgomery", "Montgomery", "Montgomery", "Montgomery", "Montgomery", "Montgomery", "Montgomery", "Montgomery", "Montgomery", "Montgomery", "Auburn", "Auburn", "Auburn", "Auburn", "Auburn", "Auburn", "Auburn", "Auburn", "Auburn", "Auburn", "Auburn", "Auburn", "Auburn", "Auburn", "Auburn", "Auburn", "Auburn", "Montgomery", "Montgomery", "Montgomery", "Montgomery", "Jacksonville", "Jacksonville", "Jacksonville", "Jacksonville", "Jacksonville", "Jacksonville", "Jacksonville", "Jacksonville", "Jacksonville", "Jacksonville", "Jacksonville", "Jacksonville", "Jacksonville", "Jacksonville", "Livingston", "Livingston", "Livingston", "Livingston", "Livingston", "Livingston", "Montevallo", "Montevallo", "Montevallo", "Montevallo", "Florence", "Florence", "Florence", "Florence", "Florence", "Florence", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Birmingham", "Mobile", "Mobile", "Mobile", "Mobile", "Mobile", "Mobile", "Mobile", "Mobile", "Mobile", "Mobile", "Mobile", "Mobile", "Mobile", "Troy", "Troy", "Troy", "Troy", "Troy", "Troy", "Troy", "Troy", "Troy", "Troy", "Troy", "Troy", "Troy", "Troy", "Tuskegee", "Anchorage", "Anchorage", "Anchorage", "Anchorage", "Anchorage", "Anchorage", "Fairbanks", "Fairbanks", "Juneau", "Juneau", "Juneau", "Juneau", "Anchorage", "Anchorage", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tempe", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Tucson", "Flagstaff", "Flagstaff", "Flagstaff", "Flagstaff", "Flagstaff", "Flagstaff", "Flagstaff", "Flagstaff", "Flagstaff", "Flagstaff", "Flagstaff", "Flagstaff", "Flagstaff", "Flagstaff", "Flagstaff", "Flagstaff", "Flagstaff", "Prescott", "Little Rock", "Little Rock", "Little Rock", "Little Rock", "Little Rock", "Little Rock", "Little Rock", "Little Rock", "Little Rock", "Fayetteville", "Fayetteville", "Fayetteville", "Fayetteville", "Fayetteville", "Fayetteville", "Fayetteville", "Fayetteville", "Fayetteville", "Fayetteville", "Fayetteville", "Fayetteville", "Fayetteville", "Fayetteville", "Jonesboro", "Jonesboro", "Jonesboro", "Jonesboro", "Jonesboro", "Jonesboro", "Jonesboro", "Jonesboro", "Jonesboro", "Jonesboro", "Jonesboro", "Jonesboro", "Jonesboro", "Jonesboro", "Jonesboro", "Jonesboro", "Russellville", "Russellville", "Russellville", "Russellville", "Russellville", "Russellville", "Russellville", "Russellville", "Russellville", "Monticello", "Monticello", "Conway", "Conway", "Conway", "Conway", "Conway", "Conway", "Conway", "Conway", "Conway", "Conway", "Conway", "Conway", "Conway", "Conway", "Conway", "Searcy", "Searcy", "Searcy", "Searcy", "Searcy", "Searcy", "Searcy", "Searcy", "Searcy", "Arkadelphia", "Arkadelphia", "Arkadelphia", "Arkadelphia", "Arkadelphia", "Siloam Springs", "Siloam Springs", "Magnolia", "Magnolia", "Magnolia", "Magnolia", "Magnolia", "Azusa", "Azusa", "Azusa", "Azusa", "Azusa", "Azusa", "Azusa", "Azusa", "Azusa", "Azusa", "Azusa", "Azusa", "Azusa", "Azusa", "Azusa", "Azusa", "La Mirada", "La Mirada", "La Mirada", "La Mirada", "La Mirada", "La Mirada", "La Mirada", "La Mirada", "La Mirada", "La Mirada", "La Mirada", "San Francisco", "San Francisco", "Riverside", "Riverside", "Riverside", "Riverside", "Riverside", "Riverside", "Riverside", "Riverside", "Riverside", "Riverside", "Riverside", "Riverside", "Riverside", "Riverside", "Thousand Oaks", "Thousand Oaks", "Thousand Oaks", "Thousand Oaks", "Thousand Oaks", "Thousand Oaks", "Thousand Oaks", "Thousand Oaks", "Thousand Oaks", "San Luis Obispo", "San Luis Obispo", "San Luis Obispo", "San Luis Obispo", "San Luis Obispo", "San Luis Obispo", "San Luis Obispo", "San Luis Obispo", "San Luis Obispo", "San Luis Obispo", "San Luis Obispo", "San Luis Obispo", "San Luis Obispo", "San Luis Obispo", "San Luis Obispo", "Bakersfield", "Bakersfield", "Bakersfield", "Bakersfield", "Bakersfield", "Bakersfield", "Turlock", "Turlock", "Turlock", "Turlock", "San Bernardino", "San Bernardino", "San Bernardino", "San Bernardino", "San Bernardino", "San Bernardino", "San Bernardino", "San Bernardino", "San Bernardino", "San Bernardino", "San Bernardino", "San Bernardino", "San Bernardino", "San Bernardino", "San Bernardino", "Pomona", "Pomona", "Pomona", "Pomona", "Pomona", "Pomona", "Pomona", "Pomona", "Pomona", "Chico", "Chico", "Chico", "Chico", "Chico", "Chico", "Carson", "Carson", "Carson", "Carson", "Carson", "Carson", "Carson", "Carson", "Carson", "Carson", "Carson", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Fullerton", "Hayward", "Hayward", "Hayward", "Hayward", "Hayward", "Hayward", "Hayward", "Hayward", "Hayward", "Hayward", "Hayward", "Hayward", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Long Beach", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Northridge", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Sacramento", "Berkeley", "Berkeley", "Berkeley", "Berkeley", "Davis", "Davis", "Davis", "Davis", "Davis", "Davis", "Davis", "Davis", "Davis", "Davis", "Irvine", "Irvine", "Irvine", "Irvine", "Irvine", "Irvine", "Irvine", "Irvine", "Irvine", "Irvine", "Irvine", "Irvine", "Irvine", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Los Angeles", "Riverside", "Riverside", "Riverside", "Riverside", "La Jolla", "La Jolla", "La Jolla", "La Jolla", "La Jolla", "La Jolla", "La Jolla", "La Jolla", "La Jolla", "La Jolla", "La Jolla", "La Jolla", "La Jolla", "La Jolla", "Santa Barbara", "Santa Cruz", "Santa Cruz", "Orange", "Orange", "Orange", "Orange", "Orange", "Orange", "Orange", "Orange", "Irvine", "Irvine", "Irvine", "Irvine", "Irvine", "Irvine", "Irvine", "Claremont", "Claremont", "Claremont", "Claremont", "Claremont", "Claremont", "Claremont", "Claremont", "Claremont", "San Rafael", "San Rafael", "San Rafael", "San Rafael", "San Rafael", "San Rafael", "Santa Barbara", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "Fresno", "San Francisco", "San Francisco", "San Francisco", "San Francisco", "San Francisco", "San Francisco", "San Francisco", "San Francisco", "San Francisco", "Oakland", "Oakland", "Oakland", "Oakland", "Arcata", "Arcata", "Arcata", "Arcata", "Arcata", "Arcata", "Arcata", "Arcata", "Pleasant Hill", "Pleasant Hill", "Pleasant Hill", "La Verne", "La Verne", "La Verne", "La Verne", "La Verne", "La Verne", "La Verne", "La Verne", "Riverside", "Riverside", "Riverside", "Santa Clarita", "Santa Clarita", "Los Angeles...
#> $ locale <dbl+lbl> 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 12, 12, 12, 12, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 43, 43, 43, 43, 43, 43, 21, 21, 21, 21, 13, 13, 13, 13, 13, 13, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 32, 11, 11, 11, 11, 11, 11, 23, 23, 33, 33, 33, 33, 11, 11, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 12, 12, 12, 12, 12, 12, 12, 12, 12, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 33, 33, 33, 33, 33, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12, 12, 12, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 11, 11, 11, 11, 11, 11, 23, 23, 23, 23, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 21, 21, 21, 21, 21, 21, 21, 21, 21, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 12, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 22, 13, 13, 12, 12, 12, 12, 12, 12, 12, 12, 11, 11, 11, 11, 11, 11, 11, 21, 21, 21, 21, 21, 21, 21, 21, 21, 13, 13, 13, 13, 13, 13, 13, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 33, 33, 33, 33, 33, 33, 33, 33, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 11, 11, 11, 21, 21, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 21, 21, 21, 21, 21, 21, 21, 21, 21, 11, 11, 11, 11, 11, 11, 11, 21, 21, 21, 21, 21, 21, 21, 21, 21, 11, 11, 11, 11, 11, 13, 13, 13, 13, 13, 13, 13, 13, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12, 13, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 12, 12, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 33, 33, 33, 33, 33, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 21, 21, 21, 21, 21, 21, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 33, 33, 33, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 31, 31, 21, 21, 21, 21, 21, 21, 21, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 13, 13, 13, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 13, 13, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 13, 13, 13, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 13, 13, 13, 13, 13, 13, 13, 13, 12, 12, 12, 12, 12, 12, 12, 12, 12, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 12, 12, 12, 21, 21, 21, 21, 21, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 21, 21, 21, 21, 21, 21, 21, 21, 13, 13, 13, 13, 13, 12, 12, 12, 12, 12, 12, 11, 11, 11, 11, 11, 11, 11, 11, 11, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 11, 11, 11, 11, 11, 11, 23, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 21, 21, 21, 21, 21, 12, 12, 12, 12, 12, 12, 12, 12, 12, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 31, 31, 31, 31, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 32, 32, 32, 32, 32, 32, 32, 12, 12, 12, 32, 32, 32, 32, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 11, 11, 11, 11, 11, 33, 33, 33, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 13, 13, 13, 13, 13, 13, 13, 13, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 22, 22, 22, 22, 22, 22, 22, 22, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 12, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 21, 21, 21, 21, 21, 21, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 21, 21, 21, 21, 21, 21, 21, 21, 21, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 1...
#> $ urban <dbl+lbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 1, 1, 1, 1, 1, 3, 3, 4, 4, 4, 4, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 4, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 4, 4, 4, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 4, 4, 4, 4, 4, 4, 4, 2, 2, 2, 4, 4, 4, 4, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 1, 1, 1, 1, 4, 4, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 2, 4, 4, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 4, 4, 4, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 4, 4, 4, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 4, 4, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 1, 1, 1, 1, 1, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 3, 4, 4, 4, 4, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 4, 4, 4, 4, 4, 4, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 4, 4, 4, 4, 4, 4, 4, 4, 4, 2, 2, 2, 2, 2, 2, 2, 2, 2,...
#> $ cipdig2 <chr> "09", "11", "13", "13", "14", "19", "26", "31", "42", "44", "51", "52", "09", "13", "13", "13", "13", "13", "13", "14", "23", "26", "26", "30", "44", "45", "51", "51", "51", "51", "51", "51", "51", "52", "52", "52", "19", "52", "13", "51", "52", "52", "13", "13", "44", "44", "51", "13", "13", "13", "13", "19", "22", "23", "25", "42", "44", "44", "50", "51", "51", "51", "51", "52", "52", "52", "52", "13", "13", "13", "13", "13", "24", "31", "42", "43", "52", "52", "04", "13", "13", "13", "13", "13", "13", "14", "26", "26", "30", "42", "51", "51", "52", "52", "52", "43", "51", "52", "52", "13", "13", "13", "13", "13", "13", "13", "26", "31", "42", "43", "44", "51", "52", "13", "13", "13", "13", "13", "13", "13", "13", "51", "52", "13", "13", "13", "31", "51", "52", "13", "13", "13", "39", "44", "51", "51", "51", "52", "52", "11", "13", "13", "13", "13", "13", "13", "23", "51", "51", "51", "51", "52", "09", "13", "13", "13", "31", "42", "43", "44", "44", "45", "51", "52", "52", "52", "51", "13", "13", "13", "44", "51", "52", "13", "52", "13", "13", "13", "44", "42", "52", "03", "04", "04", "04", "04", "05", "09", "09", "09", "11", "13", "13", "13", "13", "13", "13", "13", "13", "13", "14", "14", "14", "14", "14", "14", "14", "14", "14", "15", "19", "19", "19", "22", "22", "22", "23", "24", "26", "26", "30", "42", "42", "43", "43", "44", "44", "44", "45", "45", "45", "50", "50", "50", "50", "51", "51", "52", "52", "52", "52", "52", "52", "52", "52", "52", "54", "03", "04", "04", "11", "13", "13", "13", "13", "13", "14", "22", "25", "26", "44", "45", "45", "50", "50", "51", "51", "51", "51", "52", "52", "13", "13", "13", "13", "13", "13", "14", "23", "23", "26", "42", "45", "50", "51", "51", "51", "52", "51", "13", "13", "13", "13", "44", "44", "44", "51", "52", "13", "13", "13", "13", "15", "31", "31", "44", "50", "51", "51", "52", "52", "52", "01", "13", "13", "13", "13", "13", "13", "19", "23", "31", "43", "44", "44", "51", "51", "52", "13", "13", "13", "13", "13", "13", "43", "51", "52", "13", "31", "13", "13", "13", "13", "13", "13", "19", "25", "45", "50", "51", "51", "51", "51", "52", "13", "13", "13", "13", "51", "51", "51", "51", "52", "13", "13", "31", "42", "51", "51", "52", "13", "13", "13", "31", "52", "13", "13", "13", "39", "42", "42", "44", "45", "50", "50", "51", "51", "52", "52", "52", "52", "13", "38", "38", "39", "39", "39", "39", "39", "51", "52", "52", "42", "51", "09", "09", "13", "13", "23", "31", "42", "44", "51", "51", "51", "52", "52", "52", "13", "13", "13", "13", "42", "51", "52", "52", "52", "01", "04", "13", "13", "14", "14", "14", "14", "23", "26", "42", "52", "52", "52", "52", "13", "13", "42", "44", "44", "52", "13", "44", "44", "52", "13", "13", "13", "13", "13", "42", "44", "44", "45", "45", "51", "51", "51", "52", "52", "04", "11", "13", "14", "23", "26", "42", "52", "54", "31", "42", "44", "45", "51", "52", "13", "19", "24", "30", "42", "44", "44", "51", "51", "51", "52", "13", "13", "13", "13", "23", "31", "42", "44", "44", "50", "51", "51", "51", "52", "03", "09", "13", "13", "13", "13", "14", "14", "14", "14", "23", "26", "27", "27", "31", "42", "42", "44", "44", "45", "50", "50", "50", "51", "51", "51", "51", "52", "52", "52", "54", "13", "13", "13", "27", "44", "44", "51", "51", "52", "52", "52", "52", "09", "13", "13", "13", "13", "13", "13", "13", "13", "23", "23", "27", "27", "31", "42", "43", "44", "44", "45", "50", "50", "50", "51", "51", "51", "51", "51", "52", "09", "13", "13", "13", "13", "14", "14", "16", "23", "27", "38", "44", "44", "45", "45", "45", "45", "50", "50", "50", "51", "51", "51", "52", "54", "09", "13", "13", "13", "13", "13", "14", "14", "19", "23", "24", "42", "42", "44", "44", "50", "50", "50", "51", "51", "51", "52", "52", "52", "52", "54", "13", "13", "13", "13", "14", "16", "19", "23", "23", "26", "42", "43", "44", "44", "45", "45", "51", "51", "52", "54", "09", "14", "14", "14", "13", "14", "43", "50", "51", "51", "51", "51", "52", "52", "04", "13", "26", "30", "42", "44", "45", "50", "51", "51", "51", "52", "52", "04", "04", "05", "11", "13", "14", "14", "14", "22", "25", "44", "44", "50", "50", "50", "50", "51", "51", "52", "13", "23", "44", "52", "11", "11", "13", "14", "14", "14", "22", "26", "26", "40", "45", "50", "51", "52", "03", "13", "45", "13", "13", "23", "50", "50", "51", "51", "52", "13", "13", "13", "13", "30", "31", "52", "05", "23", "27", "42", "50", "50", "51", "52", "52", "13", "24", "42", "51", "51", "52", "42", "13", "13", "13", "31", "51", "51", "51", "52", "52", "22", "42", "44", "52", "52", "52", "52", "52", "52", "13", "42", "51", "52", "03", "13", "31", "42", "44", "45", "45", "52", "30", "31", "42", "13", "13", "19", "44", "51", "51", "52", "52", "13", "39", "52", "39", "39", "13", "13", "13", "13", "13", "13", "13", "14", "22", "22", "42", "50", "50", "51", "51", "52", "13", "13", "23", "30", "44", "50", "52", "13", "13", "13", "23", "24", "42", "50", "52", "09", "11", "11", "13", "13", "13", "13", "13", "13", "13", "15", "15", "23", "23", "27", "30", "31", "42", "42", "43", "43", "43", "44", "50", "50", "51", "51", "51", "51", "52", "52", "52", "52", "54", "13", "42", "44", "51", "52", "13", "39", "42", "52", "13", "13", "22", "45", "51", "51", "52", "13", "13", "13", "30", "42", "42", "44", "52", "52", "13", "13", "31", "51", "52", "13", "13", "13", "13", "45", "51", "52", "52", "09", "13", "13", "13", "13", "13", "13", "16", "23", "31", "42", "42", "44", "44", "45", "45", "50", "51", "51", "51", "51", "52", "52", "52", "13", "13", "13", "13", "13", "13", "13", "22", "30", "42", "43", "43", "51", "51", "51", "52", "52", "52", "05", "13", "13", "13", "23", "23", "26", "30", "31", "38", "42", "44", "44", "50", "51", "51", "51", "51", "52", "52", "03", "05", "09", "11", "13", "13", "13", "13", "13", "13", "13", "22", "26", "30", "30", "31", "42", "44", "45", "45", "51", "51", "52", "52", "52", "04", "09", "13", "13", "25", "31", "44", "51", "51", "51", "52", "52", "13", "13", "14", "14", "39", "42", "52", "42", "13", "13", "13", "13", "23", "24", "52", "52", "52", "13", "13", "23", "42", "51", "52", "42", "51", "04", "04", "04", "04", "09", "09", "09", "11", "13", "13", "13", "13", "13", "14", "14", "14", "14", "14", "14", "14", "22", "25", "26", "26", "30", "30", "30", "42", "44", "44", "44", "44", "45", "50", "50", "50", "51", "51", "51", "51", "51", "51", "51", "52", "52", "52", "52", "52", "52", "52", "52", "52", "04", "52", "13", "13", "24", "42", "52", "03", "04", "04", "04", "11", "13", "13", "13", "13", "13", "14", "14", "24", "25", "26", "26", "26", "43", "44", "45", "45", "45", "50", "51", "51", "52", "52", "52", "52", "52", "52", "54", "09", "13", "13", "13", "30", "42", "44", "45", "51", "52", "54", "03", "09", "11", "13", "14", "14", "14", "14", "14", "23", "50", "50", "51", "52", "52", "52", "13", "13", "42", "52", "11", "14", "14", "15", "40", "45", "01", "03", "03", "09", "11", "13", "13", "14", "14", "19", "23", "23", "26", "26", "26", "26", "27", "30", "30", "30", "44", "50", "50", "51", "52", "52", "54", "03", "09", "09", "11", "13", "13", "22", "22", "23", "24", "25", "30", "42", "42", "44", "44", "44", "45", "45", "45", "45", "50", "50", "51", "52", "52", "52", "52", "52", "52", "52", "52", "52", "13", "44", "52", "23", "42", "50", "13", "13", "13", "13", "13", "13", "16", "26", "31", "42", "50", "51", "51", "52", "11", "13", "13", "13", "26", "30", "42", "45", "51", "51", "52", "52", "13", "51", "52", "03", "13", "23", "43", "44", "51", "52", "52", "13", "13", "13", "19", "45", "51", "51", "51", "52", "09", "13", "13", "13", "13", "13", "26", "27", "42", "43", "51", "51", "52", "52", "52", "54", "13", "14", "31", "42", "44", "44", "50", "51", "51", "51", "52", "52", "52", "52", "13", "52", "13", "23", "42", "51", "51", "52", "52", "04", "13", "13", "42", "50", "50", "51", "51", "52", "52", "52", "14", "26", "42", "43", "43", "43", "44", "51", "52", "52", "09", "09", "13", "13", "13", "26", "26", "44", "51", "51", "51", "52", "52", "52", "09", "09", "13", "26", "42", "43", "43", "51", "51", "51", "51", "52", "52", "52", "13", "13", "13", "26", "30", "42", "44", "51", "51", "52", "13", "13", "13", "13", "23", "23", "31", "40", "42", "44", "51", "51", "51", "52", "13", "42", "52", "03", "04", "04", "26", "38", "39", "39", "50", "50", "50", "50", "50", "51", "51", "51", "51", "52", "31", "44", "13", "13", "13", "42", "44", "50", "50", "51", "51", "52", "13", "13", "13", "13", "13", "13", "13", "43", "43", "44", "44", "45", "51", "51", "51", "51", "52", "52", "52", "52", "52", "52", "03", "09", "09", "09", "09", "10", "13", "13", "13", "13", "19", "22", "23", "30", "38", "42", "43", "43", "44", "44", "45", "45", "45", "45", "50", "50", "50", "51", "52", "52", "52", "52", "52", "54", "39", "42", "50", "51", "52", "52", "13", "44", "51", "16", "44", "51", "52", "03", "05", "09", "09", "09", "11", "11", "13", "13", "13", "13", "13", "13", "13", "14", "15", "22", "22", "26", "26", "30", "42", "43", "43", "43", "44", "44", "45", "45", "45", "45", "50", "50", "51", "51", "51", "51", "51", "51", "51", "51", "52", "52", "52", "52", "52", "54", "04", "05", "09", "09", "11", "15", "22", "23", "24", "26", "26", "26", "26", "26", "27", "30", "30", "30", "31", "43", "44", "45", "45", "45", "51", "51", "51", "52", "52", "52", "52", "52", "52", "39", "44", "45", "50", "51", "51", "51", "52", "13", "13", "13", "13", "51", "51", "52", "52", "13", "13", "26", "26", "31", "42", "44", "44", "51", "51", "51", "52", "09", "42", "52", "11", "13", "13", "13", "13", "13", "13", "13", "13", "15", "23", "26", "31", "42", "43", "44", "44", "50", "51", "51", "51", "51", "51", "52", "52", "52", "52", "52", "14", "14", "15", "42", "45", "49", "52", "52", "04", "31", "42", "44", "45", "51", "51", "51", "52", "04", "13", "13", "13", "13", "13", "14", "26", "31", "43", "44", "45", "45", "45", "51", "51", "51", "51", "52", "52", "52", "52", "11", "15", "42", "52", "52", "52", "52", "04", "04...
#> $ cipcode <chr> "0901", "1101", "1304", "1312", "1499", "1901", "2601", "3105", "4228", "4407", "5102", "5202", "0901", "1304", "1310", "1311", "1312", "1313", "1314", "1401", "2301", "2601", "2612", "3019", "4404", "4511", "5107", "5109", "5110", "5122", "5123", "5131", "5138", "5202", "5203", "5212", "1907", "5202", "1312", "5138", "5202", "5213", "1304", "1312", "4407", "4499", "5123", "1304", "1310", "1312", "1313", "1901", "2202", "2313", "2501", "4228", "4404", "4407", "5005", "5102", "5123", "5138", "5199", "5202", "5203", "5213", "5214", "1304", "1305", "1310", "1311", "1312", "2401", "3105", "4201", "4301", "5201", "5203", "0410", "1301", "1304", "1310", "1311", "1312", "1313", "1404", "2601", "2609", "3019", "4201", "5102", "5138", "5202", "5203", "5212", "4301", "5115", "5202", "5213", "1301", "1304", "1305", "1310", "1311", "1312", "1313", "2601", "3105", "4201", "4301", "4404", "5138", "5201", "1304", "1305", "1310", "1311", "1312", "1313", "1311", "1312", "5102", "5202", "1301", "1304", "1312", "3199", "5138", "5202", "1304", "1310", "1312", "3906", "4407", "5102", "5123", "5138", "5202", "5203", "1101", "1304", "1310", "1311", "1312", "1313", "1399", "2301", "5102", "5109", "5123", "5138", "5203", "0901", "1304", "1311", "1312", "3105", "4228", "4301", "4404", "4407", "4501", "5138", "5202", "5203", "5210", "5123", "1301", "1304", "1311", "4407", "5138", "5213", "1311", "5202", "1304", "1310", "1312", "4404", "4228", "5202", "0301", "0402", "0403", "0409", "0410", "0502", "0901", "0904", "0909", "1107", "1303", "1304", "1305", "1309", "1310", "1311", "1312", "1313", "1314", "1401", "1402", "1405", "1407", "1408", "1409", "1410", "1413", "1419", "1599", "1904", "1905", "1907", "2200", "2202", "2299", "2301", "2401", "2611", "2699", "3000", "4201", "4228", "4301", "4303", "4404", "4405", "4407", "4507", "4509", "4511", "5004", "5005", "5007", "5009", "5102", "5122", "5201", "5202", "5203", "5208", "5209", "5211", "5213", "5216", "5220", "5401", "0301", "0402", "0406", "1101", "1301", "1304", "1310", "1312", "1313", "1410", "2299", "2501", "2699", "4404", "4507", "4509", "5007", "5009", "5102", "5115", "5122", "5138", "5202", "5203", "1302", "1304", "1310", "1311", "1312", "1313", "1401", "2313", "2399", "2601", "4228", "4502", "5009", "5102", "5109", "5138", "5202", "5115", "1304", "1305", "1311", "1312", "4404", "4407", "4499", "5123", "5202", "1304", "1311", "1312", "1313", "1515", "3103", "3105", "4407", "5009", "5102", "5109", "5202", "5203", "5213", "0101", "1303", "1304", "1310", "1311", "1312", "1313", "1907", "2301", "3105", "4303", "4404", "4407", "5102", "5138", "5202", "1301", "1304", "1305", "1311", "1314", "1399", "4303", "5107", "5202", "1312", "3105", "1301", "1304", "1310", "1311", "1312", "1313", "1901", "2599", "4507", "5009", "5102", "5115", "5123", "5138", "5202", "1304", "1311", "1312", "1313", "5102", "5109", "5115", "5138", "5202", "1304", "1312", "3105", "4227", "5115", "5115", "5202", "1305", "1311", "1312", "3105", "5202", "1301", "1313", "1314", "3906", "4228", "4299", "4407", "4599", "5007", "5009", "5109", "5138", "5201", "5202", "5203", "5210", "1301", "3800", "3899", "3902", "3903", "3906", "3907", "3999", "5102", "5201", "5203", "4228", "5133", "0901", "0909", "1301", "1311", "2301", "3105", "4228", "4404", "5109", "5122", "5138", "5201", "5202", "5203", "1304", "1310", "1311", "1312", "4228", "5115", "5202", "5208", "5210", "0109", "0403", "1301", "1313", "1401", "1408", "1410", "1419", "2301", "2601", "4201", "5202", "5203", "5213", "5216", "1301", "1311", "4228", "4404", "4407", "5202", "1301", "4404", "4407", "5202", "1301", "1304", "1305", "1310", "1313", "4228", "4404", "4407", "4501", "4509", "5107", "5122", "5123", "5202", "5203", "0403", "1107", "1301", "1408", "2301", "2601", "4201", "5202", "5401", "3105", "4201", "4407", "4502", "5102", "5202", "1301", "1907", "2401", "3005", "4228", "4404", "4407", "5123", "5138", "5199", "5202", "1301", "1303", "1311", "1312", "2313", "3105", "4201", "4404", "4407", "5009", "5115", "5123", "5138", "5202", "0301", "0901", "1304", "1310", "1312", "1313", "1408", "1409", "1414", "1419", "2301", "2601", "2703", "2705", "3105", "4201", "4228", "4407", "4499", "4511", "5005", "5007", "5009", "5102", "5115", "5122", "5138", "5202", "5203", "5216", "5401", "1301", "1304", "1311", "2705", "4404", "4407", "5102", "5107", "5202", "5203", "5213", "5220", "0901", "1302", "1303", "1304", "1305", "1309", "1310", "1311", "1312", "2301", "2313", "2701", "2703", "3105", "4228", "4399", "4404", "4407", "4507", "5005", "5007", "5009", "5102", "5107", "5115", "5122", "5131", "5202", "0901", "1301", "1310", "1311", "1312", "1410", "1419", "1609", "2301", "2701", "3801", "4404", "4407", "4502", "4506", "4510", "4511", "5001", "5007", "5009", "5107", "5131", "5138", "5202", "5401", "0901", "1304", "1310", "1311", "1312", "1399", "1408", "1436", "1901", "2301", "2401", "4201", "4228", "4404", "4407", "5005", "5007", "5009", "5102", 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#> $ ipedscount1 <dbl> 8, 15, 14, 28, 9, 8, 23, 11, 56, 92, 28, 30, 13, 11, 28, 26, 68, 15, 61, 122, 11, 48, 11, NA, 29, 9, 106, 64, 23, 136, 55, 42, 554, 115, 83, 35, 28, 23, 26, 96, 95, 17, 18, 19, 7, 17, 43, 36, 24, 52, 36, 200, 57, 15, 72, 19, 9, 189, 11, 25, 13, 50, 56, 152, 89, 44, 55, 12, 18, 16, 9, 29, 16, 18, 8, 23, 46, 10, 14, NA, 53, 34, 27, 59, 61, 37, 33, 53, 12, 13, 25, 55, 210, 97, 29, 38, 41, 31, 30, NA, 45, 11, 17, 18, 40, 16, 10, 39, 6, 6, 17, 13, NA, 48, 58, 52, 90, 314, 29, 41, 47, 25, 23, NA, 14, 67, 7, 37, 116, 25, 17, 46, 38, 8, NA, NA, 117, 44, 31, 89, 18, 18, 16, 37, 24, 15, 5, 21, 39, 29, 791, 10, 44, 9, 30, 106, 32, 230, 62, 68, 106, 11, 113, 134, 16, 93, 27, 19, 20, 13, 20, 14, 27, 15, 42, 17, 19, 37, 34, 13, 13, 49, 32, 26, 7, 18, 11, 3, NA, NA, 255, NA, 64, 9, 14, 20, 40, 50, 22, 28, 56, 22, 59, 51, 68, 94, 172, 10, 159, NA, 3, NA, 32, 9, NA, NA, 9, 14, 7, NA, 12, 11, 20, NA, NA, NA, NA, NA, 40, NA, NA, 34, 20, 24, 45, 37, NA, 39, 444, 91, 53, NA, 0, 288, 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17, 121, 102, 53, 0, 35, 61, 68, 54, 33, 137, 345, 39, 13, 31, 34, 30, 42, 12, 12, 27, 8, 96, 13, NA, 41, 95, 70, 19, 14, 38, 19, 109, NA, 9, 18, 58, 86, 12, 13, 16, NA, 14, 34, 37, 29, 45, 11, 17, 160, 27, 20, 54, 40, 160, 13, 15, 35, 41, 253, 92, 20, 258, 37, 7, 36, 16, 18, 34, 26, 21, 47, 29, 32, 22, 45, 14, 26, 32, 54, 120, 33, 23, 31, 24, 60, 155, NA, 31, 15, 59, 148, NA, NA, 21, 20, 17, 39, 22, 29, 31, 54, NA, 65, 266, 90, 27, 24, 19, 183, 9, 42, 50, NA, 27, 0, 46, 257, 65, 33, 20, 157, 94, 9, 24, 24, 43, 44, 4, 57, 7, NA, 77, 10, 53, 10, 12, 12, 9, 6, 82, 54, 30, 20, 67, 24, 17, NA, 29, 68, NA, 5, 11, NA, 130, NA, 51, 2, 73, 123, NA, 37, 173, 90, 463, 15, 19, 29, 23, 13, 9, 20, 14, 24, NA, 37, 159, 79, 124, 46, 64, 109, 62, 38, 72, 39, 108, 16, NA, 170, 25, NA, 213, 79, 30, 42, 146, 756, 43, 12, 97, 26, 28, 13, 12, 21, 23, 20, 23, 37, 88, 13, 47, 24, 24, 11, 19, 137, 41, 13, 49, 354, 11, 64, 18, 15, 27, 56, 40, 39, 26, 20, 18, 57, 18, 5, 47, 23, 30, 19, 1, 22, 44, 12, 27, 20, 14, 8, 27, 115, 30, 101, 14, 69, 41, 76, 20, 32, 41, 31, 89, 76, 164, 56, 11, 40, 70, 87, 124, 28, NA, 76, 76, 10, 17, 388, 148, 26, 15, 32, 188, 70, 13, 16, 326, 46, 213, 372, 123, 46, 46, 26, 16, 15, 133, 26, 172, 129, 7, 621, 29, 34, 66, 27, 299, 17, 63, 36, 27, 15, 53, 135, 50, 185, 136, 270, 34, 15, 18, 320, 463, 65, 10, 64, 62, 131, 24, 74, 4, 5, 26, NA, 11, 43, 8, 16, 18, 46, 10, NA, 28, 14, 41, 12, 8, 138, 44, 54, 76, 178, 99, 25, 137, 85, 22, 60, 245, 91, 19, 138, 36, 58, 56, 33, 103, 24, 15, 22, 31, 32, 34, 78, 40, 131, 54, 98, 94, 27, 23, 87, 182, 81, 79, 31, 19, 50, 4, NA, 14, NA, 23, 43, NA, 10, 9, 11, 16, 45, 3, 46, 26, 49, 26, 20, 67, 10, 28, 7, 7, 60, 29, 35, 43, 7, 24, 8, 27, 75, 130, 127, 243, 159, 25, 22, 86, 54, 193, 374, 22, 14, 18, 95, 19, 13, 12, 86, 58, 72, 6, 58, 62, 13, 64, 51, 50, 53, 38, 43, 87, 38, 14, 12, 30, 43, 53, 39, 90, 19, 8, 43, 21, 66, 37, 48, 38, 144, 597, 139, 111, 143, 102, 96, 12, 43, 83, 18, 0, 44, 34, 34, 20, 44, 60, 87, 95, 43, 29, 35, 13, 20, 17, 21, 16, 59, 4, 35, 11, 84, 69, NA, 8, 28, 19, 30, 32, 12, 26, 20, 21, 44, 17, 57, 270, 23, 26, 37, 111, 59, 36, 21, 14, 25, 22, NA, 37, 55, 25, 86, 167, 50, 31, 32, 33, 103, 129, 27, 57, 62, 231, 42, 105, 83, 22, NA, 118, 27, 28, 49, 11, 23, 19, 29, 13, 25, 60, 26, 215, 111, 48, 724, 103, 15, 15, 6, 33, NA, 5, 228, 48, 25, 20, 19, 4, 19, 21, 11, 21, 37, NA, 42, 130, 5, 19, 22, 23, 9, 15, 106, 16, 125, 89, 17, 10, 17, 57, 13, 28, 9, 149, 232, 68, 61, 22, 21, 78, 34, 14, 26, 8, 17, 1, 22, 10, 8, 15, 38, 22, 24, 22, 24, 3, 113, 21, 44, 91, 24, 12, 20, 130, 49, 25, 75, 111, 32, NA, 53, 45, 34, 11, 24, 10, 33, 262, 48, 17, 36, 31, 44, 223, 62, 240, 194, 76, 47, 27, 160, 706, 114, 118, 27, 20, 33, 8, 100, 65, 7, 4, 11, 134, 21, 45, 98, 22, 14, 19, 52, 238, NA, 19, 7, 95, 764, 50, 16, 43, 7, 13, NA, 9, 137, 91, 20, 21, 34, 40, 71, 13, 45, 50, 78, 18, 12, 13, 8, 81, 326, 49, 37, 14, 14, 19, 112, 5, 38, 127, 16, 13, 23, 63, 20, 5, 228, 29, 85, 264, 127, 58, 54, 57, 10, 104, 14, 47, 89, 13, 9, 119, 18, 57, NA, 24, 65, 20, 18, 19, 16, 1, 12, 48, 26, 23, 30, 44, 45, 164, 41, 52, 31, 23, 34, 233, 78, 9, 13, 12, 41, 24, 0, 6, 35, 46, 13, 86, 21, 11, 8, 31, 12, 18, 26, 19, 24, 16, 11, 17, 89, 31, 17, 46, 41, 27, 19, 37, 80, 23, 105, 27, 10, 58, 10, 12, 17, 27, 23, 77, 2, 37, 11, 70, 12, 89, 43, 33, 25, 134, 20, 9, 36, 144, 116, 0, 36, 52, 338, 86, NA, 399, 14, 12, 36, 24, 37, 46, 81, 583, 121, 115, 36, 97, 338, 200, 28, 78, 23, 26, 12, 308, 36, 22, 61, 6, 17, 15, 1, 20, 48, 28, 13, 15, 10, 27, 42, 21, 21, 11, NA, 87, 48, NA, 22, 185, 13, 30, 75, 24, 14, 17, 8, 14, 34, 13, 103, 59, 12, 15, 19, 116, 19, 4, 38, 46, 94, 20, 77, 20, 35, 31, 36, 19, 25, 50, 62, 21, 23, 25, 13, 41, 44, 101, 0, 84, 66, 193, 85, 23, 16, 21, 74, 13, 46, 28, 39, 14, 22, 37, 10, 11, 22, 21, 57, 69, 99, 11, 18, 11, 76, 50, 55, 152, 2, 15, 16, 44, 65, 245, 144, 17, 21, 30, 18, 124, 35, 10, 40, 83, 7, NA, 49, 38, 40, 27, 132, 37, 13, NA, 11, 16, 229, 23, NA, 37, 9, 39, 17, 41, 40, NA, 23, 21, 17, 30, 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#> $ ipedscount2 <dbl> 17, 9, 4, 24, 17, 10, 22, 12, 54, 79, 28, 27, 12, 30, 38, 14, 66, 42, 67, 109, 11, 44, 31, NA, 29, 14, 81, 82, 20, 138, 53, 33, 600, 133, 74, 62, 33, 23, 41, 120, 89, 28, 7, 32, 25, 5, 42, 22, 28, 65, 38, 214, 43, 19, 77, 20, 20, 225, 17, 23, 12, 64, 80, 185, 86, 41, 56, 11, 16, 18, 6, 40, 19, 18, 12, 18, 55, 16, 15, NA, 30, 39, 36, 64, 56, 32, 36, 52, 20, 14, 22, 47, 247, 79, 30, 41, 32, 74, 23, NA, 46, 11, 18, 20, 29, 16, 12, 26, 7, 8, 21, 12, NA, 70, 69, 84, 107, 306, 38, 43, 47, 24, 19, NA, 11, 59, 11, 38, 182, 32, 6, 52, 33, 13, 31, NA, 131, 48, 32, 60, 16, 12, 30, 77, 13, 9, 12, 20, 40, 30, 773, 9, 53, 12, 22, 84, 38, 203, 60, 74, 86, 8, 63, 126, 27, 90, 13, 25, 12, 6, 19, 22, 26, 6, 34, 18, 21, 30, 33, 11, 28, 40, NA, 18, 39, 21, 9, 16, NA, NA, 304, 2, 55, 4, 12, 18, 51, 36, 23, 15, NA, 18, 52, 25, 72, 83, 240, NA, 137, NA, 3, NA, 20, 11, NA, NA, 4, 9, 20, 1, 24, 9, 25, NA, NA, NA, NA, NA, 31, NA, NA, 37, 9, 24, 58, 39, NA, 36, 299, 110, 67, NA, NA, 195, 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9, 12, 27, 36, 26, 23, 16, 15, 14, 12, 106, 41, 96, 113, 73, 29, 59, 19, 36, 18, 25, 97, 109, 134, 55, 18, 82, 74, 91, 47, 63, NA, 50, 67, 16, 43, 383, 174, 16, 17, 35, 230, 72, 12, 17, 411, 44, 212, 381, 115, 53, 83, 44, 10, 22, 108, 23, 180, 101, 8, 698, 23, 27, 56, 35, 320, 13, 48, 48, 24, 20, 54, 179, 25, 173, 133, 230, 26, 43, 16, 326, 527, 65, 27, 52, 54, 178, 16, 94, 9, 9, 17, 30, 16, 38, 7, 25, 31, 19, 13, 19, 20, 11, 32, 17, 10, 104, 33, 37, 90, 130, 100, 38, 104, 130, 30, 39, 240, 96, 18, 103, 35, 61, 60, 39, 60, 15, 11, 17, 29, 25, 34, 78, 45, 143, 77, 95, 93, 25, 13, 101, 269, 67, 89, 58, 1, 52, 6, NA, 18, NA, 22, 41, NA, 14, 11, 18, 19, 49, 10, 45, 25, 58, 10, 24, 96, 17, 18, 8, 16, 64, 22, 33, 24, 12, 15, 8, 23, 118, 110, 135, 274, 194, 19, 39, 44, 54, 170, 386, 21, 14, 34, 87, 19, 18, 13, 80, 52, 54, 20, 59, 70, 17, 54, 39, 30, 36, 27, 31, 80, 37, 35, 9, 40, 39, 46, 38, 102, 0, 14, 47, 63, 85, 57, 48, 27, 136, 620, 115, 76, 140, 88, 83, 21, 123, 74, 13, 26, 74, 33, 28, 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148, 68, 47, 75, 8, 67, 12, 26, 89, 16, 14, 126, 11, 59, NA, 24, 46, 17, 25, 24, 13, 0, 15, 76, 19, 10, 23, 39, 47, 139, 48, 51, 28, 50, 60, 251, 103, 13, 16, 10, 39, 26, 0, 13, 40, 47, 39, 126, 23, 8, 5, 22, 17, 24, 17, 15, 27, 18, 13, 20, 80, 20, 4, 50, 14, 18, 35, 16, 81, 18, 68, 19, 5, 50, 6, 12, 8, 18, 17, 83, 18, 53, 31, 79, 14, 82, 39, 54, 26, 142, 17, 9, 30, 138, 120, 7, 36, 53, 379, 111, NA, 421, 10, 28, 34, 19, 3, 42, 113, 941, 143, 144, 41, 102, 354, 225, 27, 72, 33, 16, 14, 347, 56, 13, 65, 21, 32, 29, 7, 23, 49, 23, 0, 9, 24, 33, 43, 37, 25, 12, 40, 84, 31, 37, 19, 285, 18, 41, 61, 21, 24, 19, 15, 22, 53, 36, 118, 53, 17, 15, 32, 165, 22, 10, 63, 46, 129, 15, 74, 13, 45, 22, 39, 16, 27, 42, 60, 18, 23, 18, 19, 31, 44, 135, 29, 69, 55, 152, 112, 18, 24, 19, 80, 14, 43, 30, 41, 11, 20, 35, 16, 20, 19, 19, 46, 72, 91, 19, 24, 10, 60, 55, 71, 170, 14, 18, 18, 24, 70, 255, 124, 7, 17, 50, 20, 123, 40, 11, 39, 97, 9, 15, 47, 16, 61, 29, 170, 42, 11, 1, 5, 18, 226, 23, NA, 23, 8, 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#> $ debt_all_stgp_eval_n <dbl> 19, 14, NA, 45, 17, NA, 32, 16, 72, 146, 44, 43, 13, 22, 36, 22, 66, 31, 52, 116, 10, 56, 16, NA, 24, 13, 83, 112, 32, 102, 77, 16, 713, 70, 74, 52, 16, 17, 34, 138, 39, 12, 15, 40, NA, 18, 71, 45, 20, 40, 25, 123, 34, 11, 76, 13, 11, 244, 15, 29, 15, 50, 59, 103, 10, 16, 23, 14, 17, 23, 10, 45, 24, 24, 12, 26, 21, 11, 16, NA, 34, 38, 32, 52, 43, 21, 19, 30, 19, 10, 25, 77, 139, 50, 17, 37, 32, 61, 39, NA, 44, 18, 31, NA, 40, 26, 11, 38, NA, 10, 18, 13, NA, 86, 61, 81, 102, 270, 19, 42, 50, 32, 14, NA, 10, 51, 10, 31, 105, 36, 12, 60, 22, 17, 22, NA, 185, 10, 18, 11, 19, 18, 29, 64, 19, 10, 11, 27, 64, 37, 880, 10, 31, 17, 22, 75, 19, 128, 31, 55, 145, 11, 84, 77, 17, 70, 35, 16, 11, 14, 20, 10, 11, 12, 22, 15, 16, 25, 15, 14, 14, 58, 13, 13, 18, 24, 10, 29, 24, 25, 11, 1055, 206, 25, 16, 40, 55, 195, 34, 19, 47, 15, 30, 16, 19, 13, 18, 12, 31, 34, 175, 27, 37, 12, 113, 31, 51, 65, 13, 42, 54, 26, 29, 268, 222, 81, 10, 502, 35, 37, 95, 30, 15, 32, 42, 55, 114, 29, 409, 50, 23, 13, 108, 146, 25, 26, 72, 14, 14, 13, 33, 58, 36, 36, 36, 13, 15, 15, 53, 13, 22, 29, 36, 21, 21, 28, 39, 148, 273, 172, 46, 16, 280, 32, 112, 87, 82, 11, 38, 13, 10, 17, 25, 12, 78, 98, 67, 123, 14, 13, 10, 37, 23, 12, 104, 21, 36, 43, 33, 20, 109, 20, 47, 15, 11, 47, 14, 23, 30, 97, 28, 24, 18, 359, 451, 312, 28, 18, 103, 15, 12, 58, 17, 112, 27, 38, 110, 25, 27, 11, 13, 59, 31, 17, 18, 11, 11, 96, 13, 14, 10, 13, 73, 104, 15, 34, 53, 13, 14, 45, 36, 85, 46, 28, 25, 39, 89, 25, NA, 64, 12, NA, 39, 16, 13, 25, 11, 15, 95, 121, 18, 31, 47, 15, 16, 620, 81, 20, 56, NA, 144, 130, 91, 34, 16, NA, 231, 37, NA, 13, 26, 39, NA, 38, 18, NA, 70, 11, 24, 16, 28, 11, 179, 47, 19, 14, 342, 24, 10, 71, 265, 76, 30, 27, 129, NA, 110, 17, 84, 15, 49, NA, 12, 35, 11, 25, 17, 10, 13, 68, 21, 11, 23, 18, 10, 12, 11, 18, 16, 14, 17, 13, 59, 24, 11, 10, 42, 24, 68, 11, 105, 65, 17, 12, NA, 11, NA, NA, 49, 170, 10, 13, 10, 26, 19, 110, 19, 11, 12, 27, 24, 28, 18, 22, 10, NA, 12, 42, 75, 12, 28, 19, 24, NA, 13, 28, NA, 87, 99, 77, 52, NA, 38, 41, NA, 37, 16, 12, 29, 24, 19, 43, 10, NA, 19, 30, 83, 21, 17, NA, NA, NA, NA, 25, 37, 36, 11, 15, 13, NA, 10, 50, 13, NA, 124, NA, 13, 13, 14, 26, 27, NA, 18, 77, 71, 36, 22, 40, 49, 50, 44, 10, 87, 147, 44, 72, 87, 16, 15, 10, 11, NA, NA, NA, NA, NA, 20, 39, NA, 22, 11, 14, NA, 80, NA, 17, 101, 285, 32, 10, 13, 12, 51, 44, NA, 19, 12, 99, 16, 28, 53, 114, 11, 20, 11, 11, 15, 10, 10, 25, 188, 11, 10, 11, 18, 14, 10, 11, 30, 14, 65, 33, 16, 16, 22, 19, 70, NA, NA, 10, 12, 21, 47, NA, 11, 35, 346, 217, 20, 11, 55, 73, 22, 94, 40, 14, 12, 22, 10, 16, NA, NA, 108, 15, 12, NA, 13, NA, 20, 22, 11, 11, 139, 10, NA, 46, 28, 119, 18, 27, 12, 27, 13, 142, 12, NA, 12, NA, 38, 22, 17, 123, 39, 30, 138, 16, NA, NA, 14, 51, 10, 31, 27, 27, 222, 69, 40, 56, 12, NA, 221, 25, 18, 21, 17, 50, 38, 151, 20, 92, 15, 15, 150, 197, 509, 205, 28, 22, 27, 14, 13, 35, 26, 28, 23, 10, 25, 23, 12, 75, 20, 20, 59, 51, 98, 19, 16, 13, 16, 28, 54, 17, 29, 67, 423, 451, NA, 14, 28, 379, 48, 11, 12, 10, 46, 25, NA, 28, 24, 10, 18, 12, 19, 11, 68, 25, 19, 13, 15, 18, 10, NA, 13, 31, 15, 16, 24, 22, 30, 38, 52, 30, 48, 11, 69, 13, 36, 53, 14, 18, NA, 17, 25, 78, 10, 10, 26, 11, 19, 145, 32, 32, 24, 19, 19, 27, 116, 59, 18, 13, 32, 10, 10, 29, 18, 88, 25, 86, 113, 11, 11, NA, NA, 27, 16, 37, 36, 12, 75, 46, 10, 15, 12, 17, 16, 29, 28, 18, NA, NA, 21, 80, 17, 57, 29, 29, 60, 1143, NA, 346, 37, 489, 239, 124, 17, 13, 60, 52, 13, 10, 23, 87, 676, 34, 17, NA, 165, 25, 12, 36, 169, 18, 35, 241, 65, 70, 21, 14, 13, 44, 27, 33, 41, 24, 28, 82, 12, NA, NA, 25, 16, 38, 12, 11, 11, 29, 76, 22, 68, 235, 31, 330, 39, 209, 38, 48, 36, 77, 16, 15, 60, 292, 14, 37, NA, 402, 18, NA, NA, NA, 123, 30, NA, 15, 25, 14, 15, 13, 30, 122, 16, 26, 15, 41, 72, 12, 13, 73, 16, NA, 120, 72, 75, 18, NA, NA, 13, 45, 18, 63, 80, NA, 33, 23, 118, 69, 12, 11, 15, 28, 36, 35, 21, 34, 12, 11, 10, 17, NA, 29, 31, 10, 32, NA, 22, 27, 46, 11, 37, 12, 13, 13, 126, 15, 42, 24, 12, 13, 30, 12, 17, 22, 18, 108, 163, 135, 14, 10, 85, 247, 78, 33, 32, 12, 15, NA, NA, 278, 16, 47, NA, 20, 34, 34, 10, 13, 69, 15, 13, 11, 93, 73, 17, NA, NA, 50, 39, 15, 11, NA, 120, 25, 21, 40, 14, 11, 27, 32, 35, 11, NA, 41, 36, 33, 187, 47, 41, 52, 59, 17, 48, 273, 71, 44, 18, 22, 23, 20, 11, 17, 21, 38, 20, 12, 71, 13, 22, 92, 143, 53, 2410, 27, 23, 52, 142, 59, 104, 93, 46, 26, 266, 150, 30, 464, 72, 53, 14, 13, 13, 71, 15, 40, 20, 62, 206, 22, 11, 196, 25, 18, 80, 48, 13, 19, 97, 52, 34, 11, 76, 11, 13, NA, 32, 10, 25, 14, 23, 140, 10, 13, 20, 17, 199, 165, 232, 57, 21, 18, 15, 10, 16, 12, 34, 37, 54, 42, 16, 28, 13, 47, 73, 17, 21, 11, 15, 12, 26, 28, 22, 13, 12, 16, 21, 27, 38, 102, 16, 21, 22, 12, 70, 64, 11, 14, 28, 34, 13, 13, 19, 31, 53, 10, 22, 175, NA, 15, 11, 16, 29, 10, 48, 47, 31, 44, 14, 12, 10, 24, 82, 40, 12, 76, 137, 23, 18, 91, 70, 10, 86, 66, 36, 29, 21, 16, 26, 57, 27, 97, 57, 12, 10, 352, NA, 27, 16, 109, 11, 34, 25, 173, 26, 43, 37, 23, 38, 20, 22, 20, 65, 160, 52, 21, 150, 11, 122, 12, 35, 45, 26, 16, 23, 34, 62, 105, 24, 47, 18, 16, 58, 64, 50, NA, 24, 35, 39, 44, 16, 54, 226, 46, 23, 49, 17, 38, 67, 10, 10, 21, NA, 57, 12, NA, 45, 16, 51, 12, 17, 70, 17, 60, NA, NA, 10, 37, 52, 10, 15, 12, NA, 18, 49, 52, 17, 50, 10, 13, 187, 10, 10, 91, 17, 202, 14, 24, 21, 43, 96, 65, 26, 16, 53, 12, 23, 19, 15, 27, 14, 13, 46, 15, 23, 20, 26, 15, 20, 36, 18, 40, 29, 28, 36, 22, 62, 120, NA, 23, 12, 45, 17, NA, NA, 12, 18, 18, 64, 27, 40, 36, 28, NA, 47, 200, 63, 19, 11, 15, 37, 12, 68, 10, NA, 33, NA, 73, 205, 30, 30, 12, 127, 62, 11, 11, 17, 42, 55, 11, 63, 11, NA, 24, NA, 20, 12, 12, 10, 10, 10, 122, 44, 26, 17, 74, 29, 31, NA, NA, 38, NA, NA, 15, NA, 105, NA, 49, NA, 47, 23, NA, 55, 32, 160, 253, 16, 48, 21, 19, 10, NA, 11, 11, 19, 20, 10, 69, 55, 30, 49, 41, 47, 27, 37, 82, 19, 109, 10, NA, 54, NA, NA, 62, 29, 33, 12, 75, 39, 14, 13, 131, 32, 29, 10, 12, 25, 27, 20, 28, 50, 46, 17, 52, 29, 18, 15, 31, 189, 44, 17, 47, 414, 12, 59, 21, 15, 18, 121, 18, 16, 60, 10, 20, 14, 11, 11, 44, 17, 17, 12, NA, 31, 44, 17, 21, 16, 12, NA, 16, 108, 45, 34, 16, 92, 31, 61, 21, 32, 32, 28, 34, 20, 50, 55, 19, 69, 82, 78, 18, 26, NA, 59, 78, 12, 29, 335, 116, 21, 18, 39, 212, 112, 16, 16, 473, 49, 227, 226, 24, 19, 59, 11, 11, 24, 106, 13, 123, 82, 10, 213, 16, 20, 44, 29, 231, 10, 30, 16, 21, 17, 10, 167, 36, 89, 43, 218, 23, 23, 16, 494, 341, 66, 22, 51, 40, 99, 29, 146, NA, 10, 33, NA, NA, 35, 11, 34, 34, 38, NA, NA, 44, NA, 59, NA, 10, 196, 32, 67, 90, 247, 173, NA, 201, 60, 18, 32, 203, 16, 11, 100, 25, 22, 55, 18, 71, 13, 11, 13, 10, 16, 27, 49, 33, 127, 29, 103, 67, 23, 17, 52, 109, 64, 41, 19, 11, 15, 31, 30, 18, 11, 255, 270, 17, 12, 13, 21, 26, 65, NA, 57, 45, 56, 17, 23, 89, 10, 28, 10, 10, 36, 22, 35, 41, 10, 13, 12, 42, 126, 168, 105, 285, 230, 26, 32, 12, 16, 183, 146, 23, 11, 13, 100, 26, 16, 13, 72, 15, 50, 11, 56, 70, 16, 33, 54, 48, 35, 18, 13, 36, 18, 22, 10, 46, 24, 29, 25, 99, NA, 12, 77, 66, 109, 55, 84, 28, 156, 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#> $ debt_all_stgp_eval_mean <dbl> 53978, 64609, 48048, 52972, 32510, 52527, 55279, 44245, 66444, 51788, 52339, 52786, 28344, 25015, 37385, 49974, 34072, 32223, 20245, 31687, 52508, 30809, 30170, 26100, 40150, 29428, 53856, 96794, 56283, 38817, 72209, 33689, 43590, 34809, 31765, 40667, 56591, 57391, 26358, 31932, 23490, 46075, 43485, 50853, 38001, 70357, 63243, 35316, 28032, 32904, 39299, 30990, 48873, 31655, 29487, 20844, 33462, 32830, 37975, 47122, 43506, 29514, 29098, 33702, 19019, 33487, 24837, 45178, 40759, 43759, 58934, 44111, 42042, 34239, 28215, 41798, 23136, 19355, 65747, 51292, 29768, 43336, 41572, 31462, 28726, 23979, 25962, 27020, 51690, 16129, 38573, 47318, 45043, 22737, 47387, 23278, 54257, 25746, 26506, 61404, 41183, 39050, 39624, 65016, 41528, 35532, 34053, 30475, 28069, 44328, 39333, 45353, 25311, 30434, 28777, 34397, 36800, 37760, 30900, 39129, 34582, 37293, 23741, 19866, 20387, 27790, 16986, 36851, 34435, 31241, 21685, 30052, 50225, 49278, 56594, 154579, 71742, 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26450, 33706, 53329, 211...
#> $ debt_all_stgp_eval_mdn <dbl> 51568, NA, NA, 53781, NA, NA, 57016, NA, 66196, 50446, 45968, 50311, NA, 24000, 37695, 59450, 35250, 30750, 11651, 34166, NA, 30182, NA, NA, 40848, NA, 41000, 108560, 52673, 30496, 56000, NA, 41000, 30624, 34028, 41000, NA, NA, 20500, 30750, 20004, NA, NA, 48774, 41000, NA, 58158, 32654, 28775, 21000, 30750, 27564, 42892, NA, 29234, NA, NA, 30750, NA, 41000, NA, 27983, 30750, 35889, NA, NA, 20500, NA, NA, 45553, NA, 44145, 46677, 35684, NA, 35750, 20500, NA, NA, NA, 30942, 41000, 43500, 30000, 20500, 16279, 22500, 22850, 41000, NA, 37250, 49000, 41000, 20500, NA, 19800, 56000, 27500, 30750, 67250, 39705, NA, 39581, 62338, 40846, 33110, NA, 32144, NA, NA, NA, NA, 18906, 27277, 27333, 31433, 32800, 32799, 27333, 41000, 35500, 41000, NA, 16500, NA, 24316, NA, 41000, 34250, 27084, NA, 29793, 41000, NA, 51000, 172777, 71000, NA, NA, NA, 30615, NA, 54518, 40345, 17565, NA, NA, 44153, 94368, 56296, 51250, NA, 30750, NA, 58500, 34166, 41000, 56375, 47386, 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62510, 72389, 28500, 85246, 52646, NA, NA, 27993, 21112, NA, 35400, NA, 59675, 48100, 53500, 78422, 81118, NA, NA, 48215, 63201, 86864, 25881, 44999, 31331, 52347, NA, NA, 33449, 31166, 27000, 30500, NA, 20500, 41117, NA, 43437, 27666, 69305, 94019, 32500, 30500, 20500, NA, NA, NA, 134604, 134604, NA, 82034, 78548, 20500, 20500, 20500, NA, 32675, 28160, 32699, NA, NA, NA, 101000, 114000, 112250, 94216, 124900, NA, NA, NA, 60216, NA, 47994, 41000, 30500, NA, NA, NA, NA, 26700, NA, 36318, NA, NA, 63876, 61500, 41000, 41000, 53000, 50038, 32750, NA, 33006, NA, 80963, 57000, NA, NA, NA, NA, 36372, 34812, NA, NA, 20500, NA, 75166, 95583, 44077, 20500, 41000, 41000, 41000, 61981, 51548, 41000, NA, NA, 43380, NA, NA, 36670, NA, 20000, 36079, 70510, 40556, NA, NA, 65155, NA, 65733, NA, 72374, 108255, NA, 82450, 39397, NA, NA, NA, NA, NA, 40384, 34166, NA, NA, NA, 54666, 60025, NA, 40500, 28184, 36288, 35780, 33140, NA, 20920, 27832, 51250, 44842, 25920, NA, NA, 27084, 41000, NA, NA, 40500, 35082, 46920, 34416, NA, 34165, 32891, 50348, NA, 50485, 46122, NA, 84798, 40394, 41000, 36288, 36288, NA, NA, 82000, 61500, 89000, 46750, 32551, 41000, 54615, NA, 20500, 30808, 58129, NA, 81007, NA, NA, NA, 41000, 36342, 82276, 56323, 80200, 55350, 91630, 72160, 39908, 35254, 24989, 54872, 41000, NA, NA, 41000, 29551, NA, 51250, 34072, 41000, NA, 24666, NA, 18500, 28129, 52578, 13000, NA, 47567, NA, NA, NA, 34579, 26314, NA, 30750, NA, 36534, 34592, NA, NA, 53604, NA, NA, 29304, 50323, 48958, NA, 50323, 43242, NA, 71500, NA, 97141, 25934, NA, 87795, 31718, 109994, 47808, NA, NA, NA, 20500, 33903, 43556, 47155, 51500, NA, NA, NA, NA, 36738, 26456, 30750, NA, 35732, 38892, 36260, 55000, 49626, NA, 41000, NA, NA, NA, 28000, NA, 41000, 56885, NA, NA, 41030, NA, NA, 53250, NA, 50750, 79060, 44485, NA, NA, 50300, 61500, 49450, 34235, 50930, NA, NA, NA, 30951, 31429, NA, 36726, 38625, 40207, 45664, 31500, NA, NA, 28328, NA, NA, NA, 61397, 63550, NA, NA, 20500, 71500, 42433, NA, NA, NA, 59380, 40313, 26810, 35630, NA, NA, 30500, 41000, 41000, NA, 142539, 45500, 125290, 88590, 66984, 35987, 52500, 41000, 68570, NA, 89809, 69545, 63989, 50131, NA, 40750, 27911, 47595, NA, NA, 61763, 100757, 53350, NA, 63945, NA, 91437, 61936, 70712, 74115, 118698, 58578, 56250, 105547, 146535, 41000, 86500, 198810, 113188, 71750, 85254, 131635, 140524, 79041, 47394, 56496, NA, NA, NA, 41000, NA, 47394, 76000, 51250, 20500, 34166, NA, 45722, 43252, NA, 72226, 54000, NA, 29978, 28036, 20500, 22366, NA, 48184, NA, NA, NA, 26540, NA, 60613, NA, 52789, 37500, NA, NA, 49294, NA, 59065, 54295, 52152, 27165, 39281, NA, NA, NA, NA, NA, 38727, 25400, 48032, 34620, NA, 46035, NA, 54073, 39681, NA, 71031, NA, NA, NA, 26495, 30750, 30300, NA, NA, NA, 19944, 22901, 50304, 51807, NA, 27500, 33476, NA, 47357, 32518, NA, NA, 30750, 20500, NA, NA, 21360, 23500, 28008, NA, 29898, 30500, 30779, NA, NA, NA, 36020, NA, 34500, 20500, 26934, 40167, NA, NA, NA, 31578, 38435, 37142, NA, 72776, 42500, 20500, NA, 40833, 44500, NA, 52168, 46869, 41000, 64121, 83176, NA, 62401, 47539, 44838, 98486, 118089, NA, NA, 68635, NA, 79000, NA, 86039, NA, 54123, 45352, 58221, 44866, 24601, 67104, 47833, 58251, 36410, 61993, 30500, 32970, 33500, 22430, 65765, 97882, NA, 31136, NA, 25386, 28933, 58146, NA, 38189, 34010, 30770, 43794, 44238, 48152, NA, NA, 41715, 36427, 27333, NA, 43431, 62109, 62450, 43597, NA, 39206, 41000, 30657, 11000, 34478, NA, 49041, 29230, NA, NA, 36954, NA, 39934, NA, 29250, 49844, NA, 36317, NA, NA, 135500, NA, 41000, NA, NA, NA, 20500, 20500, NA, NA, NA, 35000, NA, 64728, 35313, NA, 26750, NA, NA, 26084, NA, NA, 38188, NA, 31642, NA, 41000, 36178, 38753, 41000, 21725, 26500, NA, 20500, NA, 18501, 33276, NA, 50759, NA, NA, 28500, NA, 28477, 19892, 41000, NA, 41000, 41000, NA, 20500, 20500, 24276, 58618, 27775, 39279, 38082, 41000, 35358, NA, 40867, NA, 36500, NA, NA, NA, NA, 20500, 40160, 116680, 65677, 41000, 107736, 46510, 30393, 41000, 32782, NA, NA, 20500, NA, 38500, NA, NA, 65072, NA, 64950, 31134, 20500, 20500, NA, 16374, 18323, NA, NA, NA, 47135, 45953, NA, 36140, NA, NA, 26065, 41000, 19384, NA, NA, NA, NA, NA, 30750, 43767, 30000, NA, 34572, 41000, 25600, NA, 41000, 61500, 61500, 66000, NA, NA, 35107, NA, 12000, NA, 28905, 16460, 66652, 108013, 59098, 82000, 61500, NA, 38000, 16100, 17434, NA, NA, NA, NA, 29986, 41000, NA, 30750, 33190, 27639, 18189, 30957, 35326, 36271, 21132, 29119, 33294, 29274, NA, NA, 30646, 54666, 20500, 35952, 32500, 28108, NA, 34980, 32146, NA, NA, 51250, 56096, 53000, NA, NA, 33938, 49600, 42000, 51250, 51250, 64655, NA, 61546, 56582, NA, NA, 41000, 60489, 61500, NA, 51250, 70556, NA, 63338, 41000, NA, NA, 85000, NA, NA, 41000, NA, 51250, NA, NA, NA, 61500, NA, NA, NA, NA, 52000, 30750, NA, 47049, NA, NA, NA, NA, 51685, 32148, 42386, NA, 36983, 41000, 34615, 47080, 37960, 36000, 62390, 26740, 28042, 74907, 41000, 41000, 78000, 61500, 51500, NA, 30750, 51500, 50100, 43135, NA, 50079, 59383, 52500, 93280, NA, 92513, 68778, 148048, NA, NA, 69032, 90973, 43412, 65500, 41000, 26265, 41000, NA, NA, 59700, 65780, NA, 46459, 42500, NA, 88628, NA, 61500, 66251, 66500, 69150, NA, 68560, NA, 97725, NA, NA, 50335, 76608, 69560, 74603, 71498, 65040, 50568, NA, 113479, 95310, 71562, 59445, 62260, 94835, 37940, 103533, 88398, NA, NA, 79733, 131279, 46979, 82890, NA, 34167, 68334, 24000, 41000, NA, 45001, 41001, 60760, 51250, NA, 60857, 47090, 92250, 51045, 44334, 162073, 102000, 82000, 41000, NA, 33405, 29871, NA, NA, 26710, 37469, 34922, 49801, NA, 30550, NA, NA, NA, NA, NA, 54187, 37422, 44288, 35199, 41000, 49524, 47960, 39274, NA, 32250, 33300, 39801, 14500, 31750, NA, NA, 41000, 39000, NA, NA, 36149, 34560, NA, NA, NA, 48354, 47880, 28441, NA, 47721, 66685, 33750, NA, 31346, 29239, NA, 47401, NA, NA, 25425, 30430, 29650, 40794, NA, NA, NA, 41650, 30750, 29672, 40794, 41000, 40000, 30750, 36799, NA, NA, 20500, 32000, 51250, NA, NA, 22942, 20500, NA, NA, 31415, NA, 41000, NA, 28597, 48250, NA, 28230, 58270, 56556, 33852, NA, N...
#> $ debt_all_stgp_eval_mdn10yrpay <dbl> 529, NA, NA, 552, NA, NA, 585, NA, 680, 518, 472, 517, NA, 246, 387, 610, 362, 316, 120, 351, NA, 310, NA, NA, 419, NA, 421, 1115, 541, 313, 575, NA, 421, 314, 349, 421, NA, NA, 210, 316, 205, NA, NA, 501, 421, NA, 597, 335, 295, 216, 316, 283, 440, NA, 300, NA, NA, 316, NA, 421, NA, 287, 316, 368, NA, NA, 210, NA, NA, 468, NA, 453, 479, 366, NA, 367, 210, NA, NA, NA, 318, 421, 447, 308, 210, 167, 231, 235, 421, NA, 382, 503, 421, 210, NA, 203, 575, 282, 316, 691, 408, NA, 406, 640, 419, 340, NA, 330, NA, NA, NA, NA, 194, 280, 281, 323, 337, 337, 281, 421, 365, 421, NA, 169, NA, 250, NA, 421, 352, 278, NA, 306, 421, NA, 524, 1774, 729, NA, NA, NA, 314, NA, 560, 414, 180, NA, NA, 453, 969, 578, 526, NA, 316, NA, 601, 351, 421, 579, 487, 474, 238, NA, 421, 316, NA, 474, 526, NA, NA, NA, 275, NA, NA, NA, 158, NA, NA, 249, NA, NA, NA, 544, NA, NA, NA, 564, NA, 404, 275, 349, NA, 317, 342, 355, NA, 447, 569, 329, 443, 314, 313, NA, 146, NA, 210, NA, NA, NA, 210, 301, 350, 234, 582, NA, 538, 498, 336, 579, NA, 256, 413, 460, 619, 407, 368, 401, NA, 421, 277, 516, 321, 523, NA, 498, 421, 570, 368, 320, 459, 210, 469, NA, 681, 443, 222, 259, 421, NA, NA, NA, 353, 210, 335, 357, 375, NA, NA, NA, 408, NA, 324, 251, 417, 373, 316, 365, 385, 380, 444, 421, 210, NA, 305, 283, 358, 267, 249, NA, 343, NA, NA, NA, 378, NA, 369, 792, 443, 305, NA, NA, NA, 314, 389, NA, 443, 230, 635, 416, 221, 616, 221, 190, 248, NA, NA, 277, NA, 345, 467, 397, 210, 331, NA, 158, 180, 217, 226, NA, 143, NA, NA, 244, NA, 272, 278, 326, 631, 342, 412, NA, NA, 291, 145, NA, NA, NA, NA, 223, NA, NA, NA, NA, 242, 204, NA, 218, 221, NA, NA, 361, 265, 429, 306, 210, 387, 541, 304, 221, 536, 1210, NA, NA, 357, NA, NA, 325, NA, NA, 553, 305, NA, 545, 221, NA, NA, 476, 362, 253, 654, 573, 642, 534, 317, 481, NA, NA, 614, 502, 477, NA, 375, 185, 506, 421, NA, NA, 487, NA, 421, NA, 339, NA, 888, 1161, 239, NA, 250, 491, NA, 241, 631, 287, 620, 421, 867, 328, 246, NA, 308, NA, 541, NA, NA, 457, NA, 393, NA, NA, NA, 205, 183, NA, 236, NA, NA, NA, NA, NA, NA, NA, NA, NA, 112, 313, NA, NA, 395, 240, 246, NA, 323, 319, NA, NA, NA, NA, 231, 361, 218, 367, NA, NA, NA, 328, 437, 449, 210, NA, NA, 210, 281, 381, NA, 381, NA, NA, NA, 431, 201, NA, 312, 282, 290, 488, NA, 391, NA, 418, 293, 456, 316, 973, 210, 210, 210, 195, NA, NA, 210, 339, 310, 260, NA, 293, 337, 275, 407, 300, NA, 273, 198, 210, 224, 210, 332, 328, NA, NA, NA, NA, NA, 300, NA, 490, 313, 341, NA, NA, NA, 308, 214, 415, NA, 421, 316, 380, 210, 274, 210, 215, 407, NA, 358, 407, 421, 310, 351, NA, NA, NA, NA, NA, 182, NA, NA, NA, 210, 322, 226, 328, NA, NA, 354, 275, 226, NA, 392, 293, 210, NA, NA, NA, 421, 366, 367, 303, NA, 421, NA, 210, 210, 408, NA, 316, NA, NA, NA, NA, NA, 318, 299, NA, NA, NA, NA, NA, NA, NA, 299, NA, 303, 397, NA, NA, 281, 169, 308, 228, NA, NA, NA, 379, 379, NA, NA, 421, 332, 399, 379, NA, 421, 423, 219, 293, 326, NA, NA, 384, NA, NA, NA, 305, 405, NA, NA, NA, NA, NA, 210, 411, NA, NA, 287, NA, NA, 377, 240, 316, NA, 600, NA, 272, NA, 236, NA, NA, NA, 1114, 277, 421, NA, 832, 513, 405, 236, NA, NA, NA, NA, 365, NA, 1047, 439, 642, 743, 293, 875, 541, NA, NA, 287, 217, NA, 363, NA, 613, 494, 549, 805, 833, NA, NA, 495, 649, 892, 266, 462, 322, 537, NA, NA, 343, 320, 277, 313, NA, 210, 422, NA, 446, 284, 712, 965, 334, 313, 210, NA, NA, NA, 1382, 1382, NA, 842, 807, 210, 210, 210, NA, 335, 289, 336, NA, NA, NA, 1037, 1171, 1153, 967, 1282, NA, NA, NA, 618, NA, 493, 421, 313, NA, NA, NA, NA, 274, NA, 373, NA, NA, 656, 631, 421, 421, 544, 514, 336, NA, 339, NA, 831, 585, NA, NA, NA, NA, 373, 357, NA, NA, 210, NA, 772, 981, 453, 210, 421, 421, 421, 636, 529, 421, NA, NA, 445, NA, NA, 377, NA, 205, 370, 724, 416, NA, NA, 669, NA, 675, NA, 743, 1112, NA, 847, 405, NA, NA, NA, NA, NA, 415, 351, NA, NA, NA, 561, 616, NA, 416, 289, 373, 367, 340, NA, 215, 286, 526, 460, 266, NA, NA, 278, 421, NA, NA, 416, 360, 482, 353, NA, 351, 338, 517, NA, 518, 474, NA, 871, 415, 421, 373, 373, NA, NA, 842, 631, 914, 480, 334, 421, 561, NA, 210, 316, 597, NA, 832, NA, NA, NA, 421, 373, 845, 578, 823, 568, 941, 741, 410, 362, 257, 563, 421, NA, NA, 421, 303, NA, 526, 350, 421, NA, 253, NA, 190, 289, 540, 133, NA, 488, NA, NA, NA, 355, 270, NA, 316, NA, 375, 355, NA, NA, 550, NA, NA, 301, 517, 503, NA, 517, 444, NA, 734, NA, 997, 266, NA, 901, 326, 1129, 491, NA, NA, NA, 210, 348, 447, 484, 529, NA, NA, NA, NA, 377, 272, 316, NA, 367, 399, 372, 565, 510, NA, 421, NA, NA, NA, 287, NA, 421, 584, NA, NA, 421, NA, NA, 547, NA, 521, 812, 457, NA, NA, 516, 631, 508, 352, 523, NA, NA, NA, 318, 323, NA, 377, 397, 413, 469, 323, NA, NA, 291, NA, NA, NA, 630, 653, NA, NA, 210, 734, 436, NA, NA, NA, 610, 414, 275, 366, NA, NA, 313, 421, 421, NA, 1464, 467, 1286, 910, 688, 370, 539, 421, 704, NA, 922, 714, 657, 515, NA, 418, 287, 489, NA, NA, 634, 1035, 548, NA, 657, NA, 939, 636, 726, 761, 1219, 601, 578, 1084, 1505, 421, 888, 2041, 1162, 737, 875, 1352, 1443, 812, 487, 580, NA, NA, NA, 421, NA, 487, 780, 526, 210, 351, NA, 469, 444, NA, 742, 554, NA, 308, 288, 210, 230, NA, 495, NA, NA, NA, 273, NA, 622, NA, 542, 385, NA, NA, 506, NA, 606, 557, 535, 279, 403, NA, NA, NA, NA, NA, 398, 261, 493, 355, NA, 473, NA, 555, 407, NA, 729, NA, NA, NA, 272, 316, 311, NA, NA, NA, 205, 235, 517, 532, NA, 282, 344, NA, 486, 334, NA, NA, 316, 210, NA, NA, 219, 241, 288, NA, 307, 313, 316, NA, NA, NA, 370, NA, 354, 210, 277, 412, NA, NA, NA, 324, 395, 381, NA, 747, 436, 210, NA, 419, 457, NA, 536, 481, 421, 658, 854, NA, 641, 488, 460, 1011, 1213, NA, NA, 705, NA, 811, NA, 883, NA, 556, 466, 598, 461, 253, 689, 491, 598, 374, 637, 313, 339, 344, 230, 675, 1005, NA, 320, NA, 261, 297, 597, NA, 392, 349, 316, 450, 454, 494, NA, NA, 428, 374, 281, NA, 446, 638, 641, 448, NA, 403, 421, 315, 113, 354, NA, 504, 300, NA, NA, 379, NA, 410, NA, 300, 512, NA, 373, NA, NA, 1391, NA, 421, NA, NA, NA, 210, 210, NA, NA, NA, 359, NA, 665, 363, NA, 275, NA, NA, 268, NA, NA, 392, NA, 325, NA, 421, 371, 398, 421, 223, 272, NA, 210, NA, 190, 342, NA, 521, NA, NA, 293, NA, 292, 204, 421, NA, 421, 421, NA, 210, 210, 249, 602, 285, 403, 391, 421, 363, NA, 420, NA, 375, NA, NA, NA, NA, 210, 412, 1198, 674, 421, 1106, 478, 312, 421, 337, NA, NA, 210, NA, 395, NA, NA, 668, NA, 667, 320, 210, 210, NA, 168, 188, NA, NA, NA, 484, 472, NA, 371, NA, NA, 268, 421, 199, NA, NA, NA, NA, NA, 316, 449, 308, NA, 355, 421, 263, NA, 421, 631, 631, 678, NA, NA, 360, NA, 123, NA, 297, 169, 684, 1109, 607, 842, 631, NA, 390, 165, 179, NA, NA, NA, NA, 308, 421, NA, 316, 341, 284, 187, 318, 363, 372, 217, 299, 342, 301, NA, NA, 315, 561, 210, 369, 334, 289, NA, 359, 330, NA, NA, 526, 576, 544, NA, NA, 348, 509, 431, 526, 526, 664, NA, 632, 581, NA, NA, 421, 621, 631, NA, 526, 724, NA, 650, 421, NA, NA, 873, NA, NA, 421, NA, 526, NA, NA, NA, 631, NA, NA, NA, NA, 534, 316, NA, 483, NA, NA, NA, NA, 531, 330, 435, NA, 380, 421, 355, 483, 390, 370, 641, 275, 288, 769, 421, 421, 801, 631, 529, NA, 316, 529, 514, 443, NA, 514, 610, 539, 958, NA, 950, 706, 1520, NA, NA, 709, 934, 446, 673, 421, 270, 421, NA, NA, 613, 675, NA, 477, 436, NA, 910, NA, 631, 680, 683, 710, NA, 704, NA, 1003, NA, NA, 517, 787, 714, 766, 734, 668, 519, NA, 1165, 979, 735, 610, 639, 974, 390, 1063, 908, NA, NA, 819, 1348, 482, 851, NA, 351, 702, 246, 421, NA, 462, 421, 624, 526, NA, 625, 484, 947, 524, 455, 1664, 1047, 842, 421, NA, 343, 307, NA, NA, 274, 385, 359, 511, NA, 314, NA, NA, NA, NA, NA, 556, 384, 455, 361, 421, 508, 492, 403, NA, 331, 342, 409, 149, 326, NA, NA, 421, 400, NA, NA, 371, 355, NA, NA, NA, 496, 492, 292, NA, 490, 685, 347, NA, 322, 300, NA, 487, NA, NA, 261, 312, 304, 419, NA, NA, NA, 428, 316, 305, 419, 421, 411, 316, 378, NA, NA, 210, 329, 526, NA, NA, 236, 210, NA, NA, 323, NA, 421, NA, 294, 495, NA, 290, 598, 581, 348, NA, NA, 309, NA, 354, NA, 421, 538, 446, 312, 440, NA, NA, 630, 1032, 472, 417, 773, 549, 510, 631, 388, 368, 369, 440, 435, 480, 316, 500, NA, 317, 455, 379, 339, NA, 297, 315, 310, 226, 205, 291, 249, NA, NA, NA, NA, 526, 293, NA, 284, NA, 421, 496, 421, NA, NA, 291, 354, 263, NA, 429, 631, 417, 389, NA, 526, 498, 421, 536, 957, 259, 210, 250, NA, NA, NA, NA, 315, NA, 506, 526, 333, 236, 319, 463, 274, 322, 223, 287, NA, NA, NA, NA, NA, 246, 369, NA, NA, 427, 258, 311, 314, NA, 220, NA, 388, 1428, 478, 1052, 516, 283, 352, 435, 396, 258, 397, NA, NA, 606, NA, NA, 416, NA, NA, NA, NA, NA, 411, 525, NA, 509, 1202, 400, 527, 544, NA, NA, NA, NA, NA, NA, 790, 860, 832, 430, 557, NA, NA, 487, 574, 927, NA, 531, 799, 511, 455, NA, NA, 325, 278, 309, NA, NA, NA, NA, 405, NA, NA, 464, 421, 421, 389, 284, NA, NA, 316, NA, 732, 559, NA, NA, 567, 526, 1094, 527, 526, 790, NA, NA, 526, 561, 855, NA, NA, NA, 526, 819, 631, NA, 623, 605, 606, 901, 1880, 1345, 736, 631, 1143, 544, 690, 526, 561, 667, 609, 421, 596, NA, 467, NA, NA, 631, 421, 421, NA, 579, 497, 579, 569, 610, 631, 579, 579, NA, NA, 526, 559, 421, NA, 540, NA, NA, NA, NA, NA, 365, 292, 458, 540, 379, 393, NA, NA, NA, NA, NA, NA, NA, 421, 393, 287, 316, 313, NA, 280, 320, 275, NA, 313, 318, NA, NA, 213, 515, NA, NA, 388, 385, 351, 585, 320, 202, 299, NA, NA, 230, NA, 198, 198, NA, NA, 279, NA, 232, 720, 850, 405, 239, 331, NA, NA, 210, NA, 309, 212, NA, 432, 210, 385, 418, 238, 404, NA, 410, 310, 251, 303, NA, NA, NA, NA, 312, NA, NA, 279, 266, 389, 294, 215, NA, NA, 418, 421, 613, 615, 465, 414, NA, 652, NA, 819, 733, NA, 306, 378, 421, 618, 532, 1166, 575, 421, 472, NA, 526, NA, NA, NA, 319, 421, 421, NA, 290, 497, 283, NA, 301, 348, 351, 317, 666, NA, NA, NA, 678, 549, NA, 1282, 1703, 678, 621, 668, 631, 521, 636, 515, 699, 767, 427, 614, 286, NA, 292, 648, 303, 198, 232, NA, NA, NA, NA, NA, 820, NA, 229, 221, 267, 308, 207, 210, 323, 269, 282, NA, NA, NA, 337, 285, 226, NA, NA, 358, 280, 341, 413, 385, 279, 212, 236, 211, NA, 293, 282, NA, 379, 334, NA, 298, 247, 298, NA, 299, 429, 418, 405, 418, 439, 323, NA, 300, 392, 338, NA, 390, NA, 399, 332, 366, 365, NA...
#> $ earn_count_wne_hi_1yr <dbl> NA, 13, 16, 39, NA, 11, 22, 12, 64, 138, 33, 45, 17, 32, 37, 28, 73, 18, 48, 123, NA, 20, NA, 23, 38, NA, 97, 92, 31, 114, 83, NA, 694, 87, 108, 38, NA, NA, 32, 137, 57, NA, 12, 25, NA, 17, 68, 51, 32, 52, 21, 149, 48, 15, 97, 11, 11, 276, 15, 47, 15, 47, 72, 119, 24, 41, 37, 19, NA, 24, NA, 40, 15, 26, NA, 26, 44, 11, 20, 15, 46, 34, 26, 56, 82, 41, NA, 26, NA, NA, 34, 78, 177, 89, 22, 13, 20, 32, 29, 26, 58, 13, 22, 35, 44, 26, NA, 36, NA, NA, 11, 13, 24, 74, 70, 78, 120, 290, 30, 30, 67, 33, 12, 27, NA, 72, NA, 30, 94, 49, 11, 65, 36, NA, NA, NA, 178, 15, 23, 23, 16, 12, 20, 56, NA, 13, NA, 31, 58, 45, 849, 15, 59, 30, 46, 104, 34, 199, 41, 76, 104, NA, 168, 129, 16, 88, 24, 15, 13, 12, 24, 15, 19, 12, 22, 14, 14, 45, 23, 14, 19, 64, 25, 18, NA, 20, NA, 22, 51, 14, 25, 976, 275, NA, NA, 56, 49, 210, 30, 15, 75, 30, 46, 33, 42, NA, 66, 15, 47, 55, 138, 29, 54, 11, 73, 17, 28, 70, 11, 32, 51, 13, 27, 259, 157, 105, NA, 513, 34, 24, 41, 34, 13, 29, 43, 53, 102, 37, 608, 92, 22, 13, 61, 219, 42, 30, 39, 18, 18, 17, 50, 71, 43, 51, 33, 18, 27, 19, 62, NA, 32, 53, 52, NA, 21, 38, 60, 113, 397, 208, 60, 32, 300, 30, 149, 113, 78, 16, 49, 15, 15, 17, 25, NA, 87, 69, 72, 161, 19, NA, NA, 35, 35, 19, 110, NA, 29, 49, 48, 31, 161, 19, 137, 34, NA, 31, 22, 38, 28, 91, 53, 23, 21, 407, 481, 316, 24, 13, NA, NA, NA, 36, 15, 98, 39, 40, 128, 37, 26, 24, 11, 89, 35, 12, 19, NA, NA, 87, 11, 14, 11, NA, 54, 121, 11, 39, 51, NA, 11, 42, 37, 119, 61, 25, 25, 39, 88, 22, 32, 64, 20, NA, 58, 18, 11, 29, 18, 22, 79, 151, 19, 21, 55, 18, 32, 544, 72, 19, 50, NA, 157, 132, 105, 18, NA, NA, 220, 45, 117, NA, NA, 42, NA, 42, 23, NA, 62, NA, 31, NA, 32, NA, 172, 37, 20, 17, 340, NA, NA, 43, 222, 77, 33, NA, 95, 100, 73, NA, 120, 11, 38, NA, NA, 53, 12, 36, 20, 11, 17, 75, NA, 19, 29, 31, 13, NA, 18, 22, NA, 36, NA, NA, 97, 45, 27, 32, 113, 53, 101, 18, 96, 52, 19, 68, 14, 35, 42, 27, 82, 163, 11, NA, NA, NA, 17, 128, 54, 19, 11, 45, 31, 26, 13, 25, 18, NA, 27, 42, 70, 11, 34, 22, 83, 36, NA, 40, 19, 79, 120, 93, 91, 31, 44, 135, 57, 82, 15, 24, 29, 30, NA, 99, 15, 74, 16, 36, 91, 23, 30, 83, 70, 118, 200, 57, 48, 50, 20, 25, 13, 15, NA, 52, NA, 32, 161, 30, 20, 14, 11, NA, 42, 86, 25, 115, 86, 35, 29, 37, 73, 64, 57, 29, 95, 156, 49, 83, 92, 20, NA, NA, 13, 12, 14, 19, 17, 12, 15, 60, 20, 21, 17, 16, 30, 69, 44, 17, 125, 385, 31, NA, 15, 14, 46, 57, 34, 27, 22, 85, 24, 45, 104, 129, 21, 35, 31, NA, NA, 23, 11, 27, 197, NA, NA, NA, 12, NA, NA, NA, 40, 24, 84, 24, 16, 25, 145, 48, 142, 65, 21, 18, NA, 40, 47, NA, 15, 43, 477, 271, 18, 15, 61, 150, 26, 93, 37, 26, 14, 22, 16, 21, 12, 40, 63, 21, 13, 20, 17, 13, 16, 16, NA, 17, 197, NA, NA, 51, 52, 173, 26, 63, 19, 81, 18, 164, 39, NA, 18, NA, 35, 37, 34, 76, 42, 40, 183, 12, NA, NA, 13, 61, NA, 45, 21, 27, 290, 71, 54, 87, 11, 28, 234, 48, 36, 47, NA, 70, 51, 162, 21, 69, 20, NA, 206, 226, 733, 229, 45, 15, 18, 15, 38, 40, 45, 42, 37, NA, 36, 24, 11, 109, 32, 23, 78, 79, 113, 19, 17, 29, 19, 21, 59, NA, 38, 75, 353, 461, 88, 40, 24, 585, 52, NA, NA, NA, 40, 23, 38, 26, 22, NA, 16, NA, 20, 11, 69, 17, 13, NA, 12, 13, NA, 59, NA, 28, NA, 24, 11, 27, 24, 63, 57, 24, 42, 13, 92, 16, 40, 59, 15, 32, 13, NA, 37, 86, NA, NA, 22, 16, 17, 108, 104, 90, 31, 39, 29, 40, 260, 122, 15, NA, 36, 26, NA, 20, 13, 144, 71, 79, 91, NA, NA, NA, NA, 23, 14, 26, 36, NA, 87, 34, NA, 12, NA, 22, 15, 37, 41, 33, 19, NA, 19, 40, 20, 58, 26, 28, 79, 1192, 12, 402, 37, 376, 154, 55, NA, NA, 64, 38, NA, 12, 20, 92, 401, 25, 21, 51, 198, 12, NA, 35, 141, 14, 27, 303, 69, 55, 30, NA, 18, 36, 28, 33, 38, 23, 22, 87, NA, 170, 33, NA, NA, 39, NA, 25, 15, 24, 90, 14, 57, 240, 36, 369, 24, 136, 29, 16, 40, 68, 11, NA, 12, 151, NA, 37, 134, 416, 38, 88, 19, 46, 97, 32, 60, NA, 26, 12, 18, 24, 27, 173, 12, 23, 17, 42, 79, 21, 27, 81, 29, 28, 103, 53, 74, 11, 32, 19, NA, 29, 17, 24, 39, NA, 39, 14, 114, 105, 13, NA, NA, 42, 57, 46, 12, 41, 16, NA, NA, NA, 24, 57, 47, NA, 49, 39, 29, 66, 55, 19, 45, NA, 18, 11, 105, 14, 48, 23, 20, NA, 23, 17, 21, 23, 21, 112, 167, 111, 18, 12, 50, 234, 80, 37, 14, 34, 29, 46, 88, 579, 33, 136, 52, 33, 113, 71, 25, 13, 99, 40, 14, 12, 111, 104, NA, NA, 33, 50, 56, 23, 13, NA, 172, 58, 28, 44, NA, NA, 46, 47, 47, 15, 19, 52, 22, 29, 232, 55, 41, 71, 74, NA, 31, 298, 59, 82, 37, 36, 59, 53, 17, 36, 17, 34, 21, 11, 62, 21, 14, 77, 151, 51, 2360, 24, 29, 57, 142, 54, 112, 93, 55, 40, 202, 97, 28, 501, 97, 46, 31, NA, NA, 84, 20, 81, 19, 70, 178, 28, NA, 189, 28, 16, 96, 65, 16, 37, 47, 87, 61, 32, 68, 13, 20, NA, 37, NA, 17, NA, 27, 159, NA, 12, 28, 12, 222, 190, 287, 60, 31, 11, NA, NA, 21, 15, 32, 40, 57, 52, NA, 31, 15, 57, 68, NA, NA, NA, 23, 12, 56, 55, 35, 19, 29, 14, 26, 37, 37, 144, 44, 15, 32, NA, 51, 62, NA, 33, 33, 38, 28, 15, 32, 28, 48, 18, 45, 223, 30, 26, 25, 17, 23, NA, NA, 48, 34, 22, 16, NA, NA, NA, 74, 66, NA, 82, 265, 36, 14, 94, 82, 12, 84, 76, 38, 27, 13, NA, 40, 60, 22, 101, 52, NA, 14, 408, 14, 41, 25, 144, NA, 28, 20, 200, NA, 74, 40, 31, 26, 21, 20, 32, 87, 161, 58, 15, 138, NA, 124, 14, 66, 90, 34, NA, 23, 11, 71, 81, 29, 31, 21, 22, 108, 90, 46, 12, 30, 61, 80, 55, 31, 126, 333, 45, 15, 43, 27, 41, 50, 12, NA, 40, 15, 83, 16, 39, 56, 71, 36, 12, 22, 68, 13, 65, NA, 17, 14, 61, 76, NA, NA, 13, 84, NA, 56, 62, 23, 47, NA, NA, 236, 28, 29, 87, 38, 239, 11, 25, 23, 48, 217, 106, 26, 25, 48, NA, 27, 11, 18, 24, 27, NA, 50, NA, 26, 23, 25, 16, 20, 48, 43, 132, 42, 18, 18, 12, 80, 107, 41, 15, 12, 57, 17, 76, 43, 21, 17, 13, 89, 17, 37, 44, 29, 89, 117, 262, 99, 19, 27, 24, 226, 17, 62, 20, NA, 48, NA, 74, 264, 62, 38, 13, 200, 98, NA, NA, NA, 40, 25, NA, 55, 18, 21, 52, 39, 56, NA, NA, NA, NA, NA, 117, 34, 29, 24, 78, 30, 17, 20, 98, 67, NA, 53, NA, 21, 114, 15, 63, 11, 31, 32, 29, 60, 38, 140, 259, 15, 31, 20, 29, NA, 14, 17, 18, 26, NA, 39, 111, 86, 43, 61, 63, 100, 63, 46, 80, 27, 113, 13, NA, 101, 46, 75, 154, 80, 36, 27, 147, 67, 31, 15, 138, 32, 31, 13, NA, 14, 33, 19, 37, 30, 40, 15, 54, 28, NA, 29, 17, 162, 46, NA, 34, 378, 14, 52, 26, 25, 22, 76, 19, 11, 33, 25, 23, 15, NA, NA, 53, 24, 34, 15, NA, 18, 49, 21, 27, 16, 12, 48, 16, 155, 44, 43, NA, 101, 39, 76, 30, 38, 36, 26, 67, 45, 68, 54, NA, 60, 80, 65, 53, 14, 68, 81, 82, 11, 59, 257, 129, 38, 21, 45, 192, 116, NA, 16, 289, 37, 274, 307, 34, 19, 45, 21, 13, 24, 110, NA, 159, 106, 26, 174, 20, 29, 37, 27, 89, NA, 26, 22, 34, 14, 22, 137, 51, 131, 39, 266, 27, 17, 19, 488, 418, 66, NA, 66, 20, 90, NA, 149, NA, NA, 37, 60, NA, 42, 12, 25, 24, 61, 20, NA, 48, 21, 32, 38, NA, 64, 37, 52, 107, 261, 170, 56, 252, 76, NA, 21, 208, 33, 18, 149, 20, 47, 82, 35, 105, 18, 11, 18, NA, 46, 27, 67, 57, 186, 28, 97, 89, 44, 22, 77, 143, 75, 78, 18, 14, 19, 55, 31, NA, NA, 451, 326, NA, 21, NA, 14, 20, 44, NA, 45, 53, 48, 21, 21, 76, NA, 39, NA, NA, 25, 24, 30, 62, NA, 16, NA, 38, 104, 171, 144, 299, 187, 16, 30, 17, 13, 141, 277, 25, 31, NA, 125, 25, 13, 12, 58, 24, 34, NA, 41, 82, NA, 28, 42, 42, 58, 15, 19, 42, 23, 16, 15, 46, NA, 23, NA, 77, 64, NA, 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12, NA, NA, 16, 87, 138, 37, 44, 17, 28, 37, 81, NA, 43, 154, 18, 20, 21, 99, 20, NA, 245, 50, 108, 393, 287, 87, NA, 16, NA, 70, NA, 39, 44, NA, NA, 90, 20, 55, 18, 28, 46, 28, 19, 15, 18, 26, NA, 33, 21, 17, 35, 24, 55, 90, 39, 28, 21, 23, 34, 272, 87, 14, 12, 14, 33, 27, 50, NA, 33, 36, NA, 56, 26, 13, NA, 26, 16, 25, 37, 25, 47, NA, 15, 12, 201, 30, NA, 88, 42, 39, 26, 42, 70, 25, 121, 39, 15, 61, 12, 17, NA, 33, 20, 94, NA, 36, 25, 74, 15, 68, 49, 28, 30, 35, 25, 14, NA, 149, 131, NA, 61, 97, 359, 124, 148, 197, 22, 22, 29, 28, 53, 42, 27, 187, 25, 40, 30, 32, 65, 79, 20, NA, 11, 20, 20, 322, 16, 19, 126, NA, 15, 16, 125, 49, 82, 59, 13, NA, 15, 39, 57, 34, 35, NA, 36, 124, 65, 69, 38, 366, 18, 22, 82, NA, 17, 19, 14, 33, 56, 39, 104, 51, 21, 14, 24, 48, 19, 19, 67, 61, 132, 14, 52, 23, 56, NA, 18, NA, 22, 60, 91, 22, 17, 12, 15, 34, 32, 89, 20, 108, 61, 245, 114, 27, 16, 24, 27, 22, 64, 19, 45, 15, 12, 32, 12, 20, 34, 28, 82, 60, 124, NA, NA, 11, 82, 50, 60, 248, NA, 22, NA, 33, 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#> $ earn_mdn_hi_1yr <dbl> NA, 47666, 52941, 45940, NA, 37208, 36132, 37568, 33535, 38065, 50439, 40737, 34704, 55693, 44418, 36221, 42347, 44468, 46018, 90334, NA, 18154, NA, 45794, 45852, NA, 91274, 99702, 54910, 53537, 66969, NA, 92804, 67202, 59834, 78896, NA, NA, 45980, 93383, 68499, NA, 52107, 49136, NA, 35701, 59124, 52107, 44666, 47630, 35416, 50231, 93646, 25194, 42841, 48667, 41205, 39254, 41789, 57318, 36668, 87973, 48563, 81031, 60106, 85637, 50606, 57318, NA, 47595, NA, 44989, 42682, 36132, NA, 39729, 59576, 49683, 96183, 57318, 46321, 42905, 37568, 44495, 49179, 77213, NA, 38721, NA, NA, 53358, 91363, 107636, 62409, 68219, 44942, 28960, 45529, 42682, 60399, 56189, 46589, 45696, 39909, 43601, 43240, NA, 38721, NA, NA, 52107, 56641, 63600, 59485, 46589, 46620, 52789, 46200, 49588, 36848, 42099, 52464, 53358, 63005, NA, 45102, NA, 68219, 66686, 55964, 46321, 43909, 43240, NA, NA, NA, 97565, 65053, 58447, 63005, 45696, 40089, 35274, 44520, NA, 55964, NA, 57657, 106421, 68666, 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125388, NA, 71643, 108092, 56234, 91744, 114223, 73720, 71575, 79598, 64493, 95295, 56776, 54522, 138711, 122038, 47846, 73949, NA, 46673, 53080, NA, NA, 55512, 46790, 53775, 49571, 58316, 56133, 51482, 60771, 55964, 51829, 75573, 64659, 45529, NA, 62260, 52107, NA, 52941, 52107, 61609, 58673, 52990, 49449, NA, NA, NA, NA, 75090, 19227, 31133, 48823, NA, 95295, 54996, NA, 38289, NA, 55964, 29685, 66045, 52562, 53069, 53671, NA, 72796, 49175, 33993, 71435, 50231, 73949, 88342, 60356, 67660, 84429, 76566, 63477, 55117, 47390, NA, NA, 54192, 45128, NA, 69338, 42682, 48563, 52941, 42682, 72899, 52420, 68153, 42774, NA, 63997, 49344, 60161, 90856, 65310, 58673, 63749, 83177, NA, 61516, 53775, 71015, 50856, 77401, 50856, 35600, 45539, NA, 51857, 50606, NA, NA, 68858, NA, 67420, 57318, 54035, 52502, 39369, 46478, 46884, 54463, 99335, 124590, 59485, 71854, 33993, 120922, 64493, 67660, NA, 50465, 56043, NA, 70829, 71168, 74641, 56234, 61516, 57318, 64196, 50341, 38289, 60878, NA, 33281, 41565, 48432, 74576, 56776, 50717, 39009, 52733, 52107, 70009, 59011, 52107, 97604, 79284, 69338, 104192, 67014, 49600, 53358, 51607, 49527, 54322, NA, 61516, 48849, 43128, 123527, NA, 46869, 97071, 93242, 92410, 63005, NA, NA, 51794, 59011, 57619, 53358, 44170, 84653, NA, NA, NA, 71015, 77401, 68592, NA, 72177, 51794, 61020, 119358, 76460, 63005, 63666, NA, 44384, 74573, 56494, 58673, 52733, 58943, 52107, NA, 35060, 96183, 73635, 47260, 46478, 52357, 53873, 75330, 81333, 57318, 64493, 118392, 98403, 116679, 133624, 65924, 60161, 88195, 58115, 48417, 48432, 72850, 72022, 58673, 73635, 98213, 70176, 97604, 58673, 116083, 115901, 59846, 52524, 133919, NA, NA, 67660, 56114, 57995, 30409, 69338, NA, 109763, 75432, 55512, 47846, NA, NA, 121046, 74200, 45696, 106421, 59901, 61814, 62154, 125388, 63530, 43319, 51106, 116456, 51224, NA, 55286, 47585, 36668, 99790, 76460, 80292, 107376, 91744, 72899, 94408, 47327, 40647, 55383, 47260, 48823, 62012, 49058, 64990, 71225, 61516, 51438, 157774, 62508, 29685, 30499, 18619, 104749, 122902, 50161, 98974, 54880, 74576, 161637, 128506, 68343, 60839, 72671, NA, NA, 95473, 78343, 78514, 52733, 69897, 43630, 54109, NA, 43891, 37208, 52107, 54477, 56189, 52107, 83546, 44666, 53942, 71575, 49214, 44170, 68666, 72482, NA, 63997, NA, 40017, NA, 52107, 58823, NA, 73949, 52107, 56415, 50439, 90533, 89790, 63692, 76460, 69338, NA, NA, 39009, 38289, 42682, 43798, 44728, 40548, NA, 46673, 33993, 93742, 67660, NA, NA, NA, 101072, 55964, 108852, 88416, 70456, 98403, 72482, 33900, 30771, 29685, 53358, 81391, 61922, 78971, 47260, NA, 42458, 59124, NA, 67420, 75518, 82756, 77087, 79450, 48667, 49214, 46087, 49644, 76460, 47346, 36992, 83177, 65131, 41342, 39369, NA, NA, 41565, 40467, 36848, 99683, NA, NA, NA, 43504, 38829, NA, 59756, 94851, 61380, 46478, 63600, 55964, 33993, 79473, 53497, 44276, 61064, 47260, NA, 44737, 43426, 53108, 39172, 40641, NA, 62260, 44912, 36674, 48041, 63600, 49475, NA, 23649, 67660, 90945, NA, 62357, 61020, 62260, 76460, 58943, 87399, 74307, 42256, 43888, 62409, 26933, 31523, NA, 42099, 47260, 53179, 46087, 43178, NA, 50439, 18771, 44542, 44227, 30409, 52733, 87973, 58479, 95348, 43922, 66877, 44356, 27439, 40896, 39832, 49937, 31527, 93646, 71575, 66355, 38829, 94940, 59722, 39369, 42458, 33993, NA, 42235, 26689, 65984, 66449, 67899, 45919, 47729, 50231, 42123, 61245, 118747, 40461, 54109, NA, 49136, 50856, 51722, 52684, NA, NA, 56415, 47595, NA, 47260, 188836, 74576, 69817, NA, NA, 48363, 79688, 48667, 50952, 52524, 49064, 27439, 61177, 56415, 107376, 115897, 71903, 70680, 92410, 45618, NA, 46087, 41992, 65238, 49709, 113331, NA, 71575, NA, 39369, 53358, 54192, 35420, 20140, 48265, 95295, 91211, 76878, 64990, 103078, 49840, 53108, 42479, 40551, 57318, 71957, 66653, 52524, 63005, 54522, 42682, 53775, 69535, 45934, 47260, 98403, 46738, 106421, 121226, 69606, 69218, 87112, 84653, 39369, 48823, 48639, 41007, 50231, 47260, NA, 61020, NA, 70456, 92010, 76930, 68079, 56415, 58015, 54346, NA, NA, NA, 54948, 48641, NA, 109206, 60320, 44170, 51880, 51551, 52357, NA, NA, NA, NA, NA, 50161, 48628, 59762, 102706, 63997, 50439, 55964, 69338, 66653, 64706, NA, 62260, NA, 36134, 40728, 65332, 38906, 25194, 25525, 31314, 94408, 114446, 71015, 96855, 148663, 32029, 46087, 54531, 48628, NA, 56931, 53358, 30409, 31670, NA, 93439, 92885, 54571, 59819, 59011, 51607, 49270, 46790, 55964, 44102, 59124, 41789, 53358, NA, 74786, 39214, 84653, 100213, 58866, 61218, 69338, 57564, 72543, 54974, 57318, 62479, 47260, 51273, 61516, NA, 65332, 52607, 58221, 58866, 52107, 57995, 52107, 54996, 44933, NA, 61681, 57318, 72708, 59485, NA, 80964, 61948, 50465, 48823, 30409, 47650, 57318, 89130, 64493, 81659, 82882, 110878, 47260, 39927, NA, NA, 100343, 63997, 71015, 57318, NA, 59722, 50606, 42682, 56234, 48823, 64493, 53984, 52107, 65295, 52733, 87604, NA, 55693, 53497, 57477, 52733, 56716, 65557, 46869, 101792, 99481, 85206, 52941, NA, 65387, 41379, 51607, 85760, 122038, 59576, 76190, 70863, 26353, 69338, 67846, 760...
#> $ earn_count_wne_hi_2yr <dbl> NA, NA, 11, 19, NA, NA, 25, NA, 60, 83, 36, 37, 11, 46, 29, 27, 74, 22, 46, 104, NA, NA, NA, NA, 43, NA, 74, 88, 28, 92, 60, NA, 627, 74, 79, 21, NA, NA, 14, 69, NA, NA, NA, 28, NA, NA, 46, 40, 34, 36, 20, 111, 32, 13, 98, NA, 11, 292, 17, 55, 15, 20, 72, 95, 51, 30, 48, 12, NA, 15, NA, 46, 11, NA, NA, 22, 43, NA, 21, NA, 36, 24, 30, 40, 83, 24, NA, NA, NA, NA, 23, 57, 131, 66, 16, NA, 13, 11, 12, 31, 48, NA, 16, 38, 36, 30, NA, 14, NA, NA, NA, 18, 16, 45, 62, 55, 113, 192, 33, 30, 74, 35, NA, NA, NA, 61, NA, 25, 72, 43, NA, 55, 43, NA, NA, NA, 177, 12, 19, 19, 15, NA, 13, 62, 20, 11, NA, 25, 28, 46, 646, 12, 55, 27, 27, 89, 34, 157, 28, 70, 20, NA, 138, 109, 11, 81, 13, 22, 12, NA, 27, 13, 28, 15, 16, 14, NA, 34, 14, NA, 13, 36, 48, 17, NA, 27, NA, 27, 52, NA, 19, 498, 184, 13, NA, 62, 34, 248, 15, NA, 44, 25, 40, 24, 36, NA, 41, NA, 32, 35, 64, 21, 31, NA, 40, NA, 16, 53, NA, NA, 38, NA, NA, 161, 33, 65, NA, 503, 12, NA, NA, 32, NA, 23, 36, 44, 73, 41, 552, 101, 11, NA, 14, 174, 49, NA, 16, NA, 15, 15, 40, 75, 35, 44, 25, 16, 21, NA, 67, NA, 39, 38, 38, 13, 19, 32, 48, 99, 338, 148, 55, 36, 260, 16, 136, 138, 74, NA, 53, NA, 17, 14, 21, NA, 108, 37, 48, 172, 12, NA, 16, 28, 48, 11, 107, NA, 35, 34, 33, 30, 157, 16, 127, 26, NA, 36, 15, 49, 27, 54, 41, NA, 14, 268, 321, 234, 20, 12, NA, NA, NA, 26, 11, 74, 33, 38, 120, 31, 21, 19, NA, 90, 20, NA, 18, NA, NA, 72, NA, 11, NA, NA, 50, 132, NA, 25, 39, NA, NA, 26, 20, 75, 43, 13, 24, 33, 92, 21, 24, 64, 11, NA, 50, NA, NA, 14, NA, NA, 74, 73, NA, 17, 31, NA, 27, 533, 34, 19, 30, NA, 96, 109, 75, 11, NA, NA, 150, 42, 121, NA, NA, 19, NA, 42, 22, NA, 54, NA, 24, NA, 12, NA, 135, 28, NA, 28, 285, NA, NA, 34, 213, 79, 31, NA, 41, 63, 32, NA, 98, 15, 35, NA, 15, 32, NA, 25, NA, NA, 21, 64, 17, 22, 26, 19, 17, NA, NA, 18, NA, 49, NA, NA, 64, 41, 24, 24, 88, 52, 82, 12, 94, 62, 12, 48, NA, 36, 41, 24, 50, 136, 14, NA, NA, NA, 16, 91, 54, 15, NA, 41, 23, NA, NA, 25, 19, NA, 28, 35, 97, NA, 33, 25, 90, 39, 13, 29, 16, 64, 111, 93, 82, 29, 33, 166, 35, 76, NA, 21, 17, 30, 20, 92, NA, 87, 23, 57, 85, 22, 26, 56, 31, 84, 140, 45, 31, 45, 13, 31, 18, NA, NA, 37, NA, 28, 152, 21, 18, 15, 17, 15, 29, 75, 23, 77, 72, 35, 25, 26, 70, 79, 62, 20, 53, 142, 34, 37, 53, 12, NA, NA, 12, 11, 11, NA, NA, 14, 11, 65, NA, 37, 11, 16, 30, 41, 40, NA, 97, 350, 17, NA, NA, NA, 23, 40, 22, 30, 15, 58, 15, 24, 64, 90, 13, 27, 19, NA, 11, 16, NA, 11, 154, NA, NA, NA, NA, NA, NA, NA, 24, 24, 51, 21, NA, 22, 139, 45, 145, 71, 25, 15, NA, 43, 46, NA, 13, 24, 349, 255, 21, 15, 43, 136, 23, 70, 36, 13, NA, 21, 20, 17, NA, 35, 91, 16, 11, 12, 15, NA, 12, NA, NA, 16, 193, NA, NA, 53, 28, 182, 23, 53, 16, 84, 23, 167, 48, 14, 16, NA, 29, 41, 19, 108, 38, 20, 96, NA, NA, NA, NA, 36, NA, 26, 14, 25, 159, 38, 49, 79, NA, 28, 235, 40, 36, 35, NA, 58, 63, 160, 12, 63, 19, 21, 196, 239, 654, 75, 44, NA, 14, NA, 25, 38, 39, 46, 34, NA, 29, 28, NA, 109, 30, 20, 70, 79, 58, 20, 17, 16, 22, 20, 65, NA, 25, 82, 248, 300, 43, 32, 17, 463, 37, NA, NA, NA, 42, 16, 32, 19, 31, NA, NA, NA, 17, NA, 31, NA, NA, NA, NA, NA, NA, 28, 21, 13, 14, 16, NA, 25, NA, 50, 56, 16, 34, 13, 77, NA, 22, 25, NA, 42, NA, 11, 40, 73, NA, NA, NA, 13, NA, 41, 26, 64, 24, 36, 26, 25, 272, 122, NA, NA, 21, 26, NA, 16, 17, 117, 111, 80, 90, NA, NA, NA, NA, 26, 15, 29, 31, NA, 77, 57, 12, 21, NA, 24, NA, 37, 39, 31, NA, NA, NA, NA, NA, 35, 23, 19, 49, 824, NA, 248, 23, 283, 86, 22, NA, NA, 49, 32, NA, NA, 12, 71, 236, 20, 15, NA, 148, NA, NA, NA, 74, 14, NA, 222, 51, 35, 11, NA, 14, 28, 19, 42, 48, NA, 19, 74, NA, 98, 15, NA, NA, 36, NA, 13, 17, 19, 64, NA, 58, 215, 42, 376, 15, 59, NA, NA, 19, 24, NA, NA, NA, 45, NA, 29, 152, 258, 21, 47, NA, 24, 68, 15, 21, NA, 17, NA, NA, 11, NA, 76, NA, 12, NA, 21, 47, 19, 13, 37, 17, 14, 57, 42, 64, NA, 12, NA, NA, 38, 12, NA, NA, NA, 26, 13, 117, 116, NA, 16, 15, 40, 54, 21, NA, 29, 15, 12, NA, 12, 28, 42, 45, NA, 42, 27, 24, 61, 49, 27, 38, NA, 13, 12, 82, NA, 36, 16, 14, NA, 17, 18, 13, 11, 23, 108, 144, 52, 21, NA, 11, 184, 90, 44, NA, 19, 12, 25, 47, 274, 13, 81, 23, 19, 68, 35, 11, NA, 108, 33, 15, NA, 52, 105, 15, 15, 22, 58, 26, 22, 15, NA, 134, 34, 30, 43, NA, NA, 45, 46, 40, 19, 18, 58, NA, 26, 205, 73, 40, 41, 87, NA, 33, 319, 70, 54, 35, 31, 55, 40, 22, 38, 15, 22, 14, NA, 72, 19, NA, 47, 143, 53, 2263, 24, 26, 63, 142, 47, 102, 92, 72, 27, 200, 93, 28, 638, 102, 26, 26, NA, 13, 39, 14, 75, 15, 95, 77, 12, NA, 94, 12, 12, 82, 58, 23, 33, NA, 77, 34, 29, 62, NA, 22, NA, 35, NA, 16, NA, 27, 140, 13, 12, 25, NA, 169, 157, 266, 50, 31, 12, NA, NA, 14, 14, 29, 40, 62, 43, NA, 25, 13, 55, 69, NA, NA, NA, 23, NA, 37, 58, 35, 15, 26, 13, 24, 39, 36, 165, 23, NA, 22, NA, 64, 43, 11, 22, 34, 25, 29, 16, 28, 14, 50, 16, 39, 180, NA, 23, 23, NA, 19, NA, NA, 38, 27, NA, NA, NA, NA, NA, 86, 51, NA, 55, 161, 44, NA, 73, 56, 17, 65, 108, 39, 31, NA, NA, 40, 48, 13, 82, 45, 12, 12, 393, 12, 48, 25, 128, NA, 18, 19, 182, 32, 57, 41, 32, NA, 19, 15, 23, 86, 140, 41, 14, 145, 14, 80, NA, 42, 71, 30, NA, NA, 11, 64, 70, 28, 16, 24, 17, 110, 85, 15, NA, 25, 47, 57, 55, 17, 72, 278, 33, 15, 24, 28, 22, 47, NA, NA, 23, 24, 80, NA, NA, 44, 61, NA, NA, 26, 72, NA, 28, NA, NA, NA, 39, 36, NA, NA, NA, 91, NA, 48, 62, 22, 17, 11, NA, 216, 24, 22, 69, 33, 269, NA, 24, 21, 52, 174, 86, NA, 18, 35, NA, NA, 16, 14, 14, 18, NA, 55, NA, 19, 12, 25, NA, NA, 40, 33, 105, 32, 13, NA, NA, 77, 40, 43, NA, NA, 38, NA, 42, 54, 12, 16, NA, 90, 12, 38, 30, 22, 62, 112, 164, 75, NA, 17, NA, 183, 12, 51, 13, NA, 26, NA, 37, 132, 41, 16, NA, 110, 67, 23, NA, NA, 53, 26, 16, 40, 16, 26, 43, 36, 44, NA, NA, 12, NA, NA, 97, NA, 25, 14, 52, 27, NA, NA, 67, 67, NA, 52, NA, 23, 113, 14, 63, NA, 36, 30, 30, 53, 33, 68, 226, NA, 51, NA, 18, NA, NA, NA, NA, 12, NA, 15, 35, 37, 25, 21, 29, 70, 37, 21, 32, 11, 58, NA, NA, 53, 15, 36, 71, 37, 12, 14, 67, 31, 17, 20, 92, 14, 33, 16, NA, NA, 22, 15, 31, NA, 48, 16, 46, 22, NA, 48, NA, 148, 57, NA, 29, 345, 16, 48, 20, 26, 12, 73, 25, NA, NA, 29, 19, 15, NA, 15, 23, 21, 37, 14, NA, NA, 33, 22, 28, 13, NA, 53, NA, 114, 49, 50, NA, 113, 32, 64, 30, 39, 19, 22, 99, 57, 63, 77, NA, 52, 87, 45, 61, NA, 70, 82, 94, NA, 53, 192, 128, 41, 21, 46, 164, 118, NA, 14, 155, 36, 175, 370, 39, 30, 53, 11, NA, 13, 103, NA, 146, 50, 19, 209, 18, 36, 29, 25, 59, NA, 21, 18, 34, NA, 31, 116, 22, 137, 34, 227, 14, 22, 16, 462, 389, 41, NA, 52, NA, 73, 37, 154, NA, NA, 39, 47, NA, 49, NA, 17, 17, 33, 11, NA, 46, 12, 86, 42, NA, 39, 25, 54, 141, 317, 166, 61, 272, 99, NA, NA, 136, NA, NA, 54, NA, NA, 35, 14, 36, NA, NA, NA, NA, 27, NA, 23, 30, 86, NA, 14, 21, 22, NA, 22, 55, NA, 24, NA, NA, 17, 14, NA, NA, NA, 251, 166, NA, 27, NA, 11, 15, 20, NA, 21, 27, 36, NA, 21, 52, NA, 36, 11, NA, 22, 26, 21, 60, NA, 16, NA, 16, 57, 63, 160, 216, 128, NA, 25, 14, NA, 70, 247, 23, 40, NA, 131, 21, 13, NA, 49, 19, 16, NA, 29, 79, 11, 19, 40, 25, 52, 11, 17, 34, 36, 11, 13, 38, NA, 31, NA, 64, 90, NA, NA, 42, NA, 44, 85, 12, 67, 681, 54, 31, 54, 54, 37, 28, NA, 15, 14, NA, 42, 34, 45, NA, 49, 16, NA, 106, 50, 30, 31, NA, 13, NA, NA, 27, 56, 18, 24, NA, 53, 52, 296, NA, 13, 13, 17, 27, NA, 42, 12, 33, 43, 19, 44, NA, 16, 30, NA, 91, 31, 41, NA, NA, 14, 17, 27, 21, 66, 24, 124, 56, 45, 21, 74, 47, 165, 171, NA, 26, 49, 28, 26, 21, 32, 16, NA, 106, NA, 34, 29, 14, 26, NA, 44, 23, 35, 107, 31, 213, 85, 85, 717, 135, 16, NA, NA, NA, NA, NA, 45, NA, NA, NA, NA, NA, 15, 31, NA, 39, 68, NA, 33, 217, NA, 21, NA, NA, NA, 13, 44, 18, 28, NA, NA, NA, NA, 39, NA, 16, NA, 81, 185, 25, 14, NA, 11, 55, 27, 35, 22, 15, 16, NA, 19, 17, NA, 17, NA, 21, NA, 17, 63, NA, 94, 19, 42, 54, 17, NA, 25, 226, 58, 31, 228, 153, 13, NA, 43, 38, 49, NA, NA, 11, 29, 206, 64, 24, 36, 25, 51, 275, 54, 211, 178, 31, 88, 16, 124, 590, 161, 117, 36, NA, 23, 21, 99, 76, NA, 26, NA, 128, 29, NA, 79, 26, 27, 43, 24, 188, 54, 14, NA, 57, 717, 31, 16, 66, NA, 11, 11, NA, 28, 89, 66, 55, 45, 81, 122, 12, 36, NA, 29, 15, NA, NA, 13, 82, 98, 23, 45, 12, 21, 37, 15, NA, 27, 98, 18, 21, 30, 47, NA, NA, 201, 48, 65, 403, 223, 62, 20, NA, NA, 34, NA, 11, NA, NA, NA, 67, 19, 47, 20, 23, 54, 25, 11, NA, 12, 36, 12, 29, NA, NA, 23, NA, 23, 30, 11, NA, NA, 17, 27, 235, 65, 21, NA, 14, 25, 18, 70, NA, NA, 31, NA, 59, 20, NA, NA, 21, 30, 24, 27, 31, 34, NA, 13, 17, 221, 12, NA, 61, 31, 17, 14, 17, NA, NA, 46, 15, NA, 21, NA, 15, NA, 36, NA, 66, NA, 20, 25, 63, 18, 42, 45, NA, 23, 37, 13, 11, NA, 137, 159, NA, 32, 99, 360, 125, 136, 170, 15, 34, 17, 25, 51, 39, 23, 60, 25, 40, 15, 28, 46, 75, 11, NA, NA, 15, 21, 293, NA, 11, 37, NA, NA, 16, 39, 25, 78, 47, NA, NA, NA, 31, 36, NA, 29, NA, 28, 105, 61, 62, 39, 302, NA, 16, 60, NA, NA, 18, 14, 17, 37, 45, 87, 39, 11, NA, 25, 60, NA, 18, 72, 53, 154, NA, 44, 18, 65, NA, 13, NA, 18, 71, 69, 19, 16, 19, 20, 21, 45, 74, 21, 96, 56, 318, 132, 32, 18, 22, 18, 16, 59, NA, 33, 13, 11, 28, 12, 24, 24, 22, 63, 50, 114, NA, NA, NA, 60, 22, 49, 224, 13, 24, 14, 16, 77, 130, 130, NA, 17, 36, 14, 143, 23, NA, 53, 59, NA, NA, 80, 27, 50, 36, 166, 27, NA, 275, NA, 11, 165, NA, NA, 51, NA, 62, NA, NA, 37, NA, 30, 25, NA, NA, 46, 28, 39, 16, 34, 45, 77, 21, 23, 12, 15, 26, 121, 45, 88, 132, 21, 18, 20, 11, 19, 36, 83, 11, 13, 50, 74, 20, 27, NA, 30, 13, NA, 12, 20, 14, 41, NA, NA, 27, 21, 18, 128, NA, NA, NA, NA, 28, 70, 81, 23, 38, 19, NA, 19, 22, 27, 56, NA, 20, 11, 11, 13, 17, 183, NA, NA, NA, 100, 20, NA, 29, 65, 117, 19, 37, 25, NA, 16, 42, 43, 13, 47, 11, 11, NA, NA, NA, 15, 16, 14, 21, 13, NA, 13, 20, 37, 23, NA, 21, 11, 42, 25, NA, NA, 26, 23, 414, NA, 78, 20, 18, 28, NA, 57, 27, 18, NA, 38, NA, 90, NA, 37, 27, 23, 106, 260, 109, 27, 751, 54, 24, NA, 23, 19, NA, 16, 213, 379, 101, 57, 75, 107, 96, 11, 51, 13, NA, 19, 76, NA, 48, 36, 37, NA, 59, 102, 34, 15, 60, NA, NA, 16, 11, 112, 78, 104, 20, 20, 36, 12, 23, 13, 84, NA, 127, NA, 35, 23, 26, 11, NA, 25, 58, 31, 212, 316, 91, NA, NA, NA, NA, 37, 31, 60, 28, NA, 36, 17, NA, 15, 60, 20, 34, NA, 18, 24, NA, 32, 46, NA, 29, 14, 25, 30, 95, 42, 30, 35, 54, 29, 17, 33,...
#> $ earn_mdn_hi_2yr <dbl> NA, NA, 50231, 43240, NA, NA, 35594, NA, 34793, 37819, 55036, 43798, 38289, 54154, 44170, 36852, 42682, 45305, 47260, 88820, NA, NA, NA, NA, 44869, NA, 89564, 99737, 53984, 56979, 67324, NA, 95215, 70176, 60920, 84653, NA, NA, 43240, 91017, NA, NA, NA, 50717, NA, NA, 47729, 53108, 45752, 47455, 34420, 47427, 91744, 30771, 41136, NA, 32563, 38981, 37208, 56641, 36668, 90412, 44921, 80004, 62707, 84653, 46673, 63997, NA, 46478, NA, 46087, 39729, NA, NA, 36992, 56641, NA, 70456, NA, 41844, 44021, 34603, 48041, 45249, 70456, NA, NA, NA, NA, 55151, 93520, 114892, 60854, 64791, NA, 32925, 50856, 41992, 59576, 57017, NA, 45696, 39369, 43519, 45500, NA, 39009, NA, NA, NA, 63997, 63997, 61681, 47260, 48510, 53942, 46261, 46380, 37088, 42249, 56157, NA, NA, NA, 45500, NA, 70680, 66461, 54851, NA, 43638, 39585, NA, NA, NA, 99380, 52107, 59124, 71015, 48041, NA, 36668, 43240, 36134, 57318, NA, 56641, 102706, 70232, 96954, 64990, 44885, 55512, 39099, 43387, 36995, 37131, 50606, 55102, 38289, NA, 91389, 58549, 53775, 46321, 61516, 52107, 78343, NA, 51750, 106421, 74017, 50439, 58221, 76460, NA, 52941, 63749, NA, 81333, 47260, 55151, 46478, NA, 69338, NA, 46869, 39950, NA, 106421, 48057, 51907, 57189, NA, 45655, 45149, 44805, 55286, NA, 90412, 82440, 67420, 77401, 71015, NA, 94817, NA, 81702, 50856, 39549, 54192, 41193, NA, 49136, NA, 42682, 46087, NA, NA, 47260, NA, NA, 48725, 47260, 51035, NA, 46118, 54713, NA, NA, 43426, NA, 26739, 17508, 57995, 57318, 50439, 98650, 57911, 76460, NA, 74576, 94075, 62260, NA, 38414, NA, 46673, 50439, 75518, 40821, 47260, 47494, 38829, 39585, 83388, NA, 35701, NA, 51273, 54109, 47260, 21508, 25194, 63997, 39214, 49392, 74953, 92743, 58165, 52385, 50677, 43426, 43974, 41457, 48326, NA, 41286, NA, 38289, 59124, 46478, NA, 60298, 101406, 92632, 65042, 43426, NA, 44384, 48041, 42203, 42682, 47877, NA, 38289, 54739, 44649, 42363, 44960, 58221, 69524, 42402, NA, 44595, 39927, 56776, 40089, 106421, 62463, NA, 48138, 45165, 49752, 44755, 44384, 37856, NA, NA, NA, 32569, 61516, 50022, 45383, 52107, 135614, 57318, 38649, 49136, NA, 40222, 38289, NA, 35060, NA, NA, 38870, NA, 46087, NA, NA, 41565, 41021, NA, 41725, 47260, NA, NA, 57318, 48432, 67548, 92358, 48432, 58221, 41193, 40037, 42682, 50105, 106978, 32925, NA, 67101, NA, NA, 30409, NA, NA, 39009, 74105, NA, 37568, 42458, NA, 58402, 60234, 49787, 30771, 32569, NA, 41937, 54082, 43368, 42682, NA, NA, 106724, 54585, 59425, NA, NA, 51273, NA, 53775, 41565, NA, 38289, NA, 33993, NA, 90856, NA, 35327, 36221, NA, 38289, 61060, NA, NA, 39009, 47455, 63005, 41193, NA, 111769, 57318, 73075, NA, 75011, 62012, 56641, NA, 48432, 36852, NA, 76460, NA, NA, 63749, 52941, 53810, 78971, 74200, 101964, 94408, NA, NA, 45808, NA, 70886, NA, NA, 67995, 53608, 54359, 52941, 58943, 71015, 59688, 54661, 57796, 73949, 33993, 86356, NA, 65066, 64358, 46321, 52524, 58503, 33993, NA, NA, NA, 47260, 72214, 47260, 64493, NA, 66461, 72650, NA, NA, 41565, 85357, NA, 41007, 51106, 54073, NA, 68499, 50856, 74576, 49579, 47394, 59124, 31839, 59350, 60096, 69757, 117274, 45919, 69338, 69490, 58522, 50231, NA, 32925, 30771, 66541, 52107, 56641, NA, 49064, 48432, 102409, 90049, 62012, 54661, 49854, 66541, 58912, 76325, 70176, 94408, 71015, 86129, 48041, 39927, NA, NA, 33993, NA, 46478, 55534, 61516, 38829, 31133, 33993, 24035, 68499, 47025, 50439, 114595, 80779, 66541, 71015, 46790, 64791, 90856, 60878, 78785, 68918, 64087, 70456, 56867, 79838, 63005, NA, NA, 44971, 59045, 63005, NA, NA, 44384, 71575, 60878, NA, 41565, 46087, 65053, 63005, 50439, 76930, NA, 57920, 59443, 53775, NA, NA, NA, 72403, 66821, 52464, 48432, 61516, 67660, 46087, 59722, 74367, 66461, 38289, 82440, 58673, NA, 46087, 63005, NA, 61516, 60585, NA, NA, NA, NA, NA, NA, NA, 57318, 58221, 103746, 106421, NA, 41937, 76863, 63005, 53034, 70536, 42682, 63005, NA, 52607, 33993, NA, 38289, 73769, 66078, 58035, 33459, 21508, 36848, 68608, 54869, 55383, 88907, 60094, NA, 86867, 41565, 69338, NA, 52733, 52584, 80022, 56415, 38337, 35416, NA, 54435, NA, NA, 58221, 56114, NA, NA, 66401, 90412, 73739, 47260, 49136, 72482, 78971, 85760, 53202, 72343, 55964, 29639, NA, 50022, 125015, 135393, 116258, 63005, 61516, 58092, NA, NA, NA, NA, 74307, NA, 190536, 57318, 115339, 90983, 60623, 55286, 59756, NA, 134761, 57318, 68666, 96775, 90533, NA, 49136, 61401, 59742, 15552, 42682, 30771, 26715, 77054, 99040, 143744, 58568, 40461, NA, 60320, NA, 162463, 55331, 75706, 73195, 94408, NA, 35060, 42759, NA, 59901, 28960, 79699, 101406, 57860, 54894, 61516, 53358, 58221, 46673, 26353, 36959, NA, 39729, 80459, 84854, 86222, 86550, 82440, 47260, 51857, 62012, NA, NA, NA, 55964, 19455, 46254, 59986, 61020, NA, NA, NA, 42682, NA, 73949, NA, NA, NA, NA, NA, NA, 64493, 42682, 125611, 63005, 65332, NA, 53775, NA, 88861, 71734, 63005, 84653, 47260, 79284, NA, 46478, 137605, NA, 41565, NA, 36134, 52941, 53045, NA, NA, NA, 42682, NA, 46673, 61516, 53358, 50606, 63501, 67324, 53179, 69657, 69338, NA, NA, 47260, 53168, NA, 52941, 55693, 58360, 58025, 52107, 51690, NA, NA, NA, NA, 77487, 25824, 31670, 49883, NA, 93646, 56579, 68219, 34526, NA, 64493, NA, 64493, 52385, 56579, NA, NA, NA, NA, NA, 67660, 53775, 71575, 84653, 60312, NA, 83505, 66821, 61547, 57072, 48935, NA, NA, 50231, 35060, NA, NA, 42682, 51106, 49730, 42712, 61516, NA, 75989, NA, NA, NA, 49370, 60161, NA, 65238, 59824, 65657, 73949, NA, 60094, 48432, 76460, 43128, 78074, NA, 48432, 40945, NA, 54610, 49136, NA, NA, 68858, NA, 76460, 48823, 44649, 54622, NA, 47260, 45305, 57318, 92733, 122038, 61681, NA, NA, 118210, 69338, NA, NA, NA, 56302, NA, 70009, 73562, 79037, 49214, 67995, NA, 64196, 47260, 46478, 65486, NA, 16663, NA, NA, 76460, NA, 49990, NA, 50856, NA, 70456, 52733, 51273, 104192, 68499, 67899, 76460, 68079, 53775, 49392, NA, 45715, NA, NA, 84653, 45696, NA, NA, NA, 38906, 94408, 91744, 89672, NA, 89530, 50856, 53984, 59726, 53775, NA, 50231, 76460, 29593, NA, 12961, 68219, 72605, 70680, NA, 68858, 49621, 41565, 112270, 80124, 70296, 70009, NA, 57318, 140922, 56415, NA, 51392, 61020, 57318, NA, 41342, 97959, 79450, 39927, 57318, 54109, 48510, 79284, 67660, NA, 50856, 122038, 96866, 91744, NA, 62012, 66077, 86550, 57072, 46013, 49058, 72320, 73635, 56415, 71015, 87973, 68778, NA, 59280, 104192, 116083, NA, 48667, 128588, 47260, 52107, 69338, 52562, 57705, 26353, 94408, NA, 108331, 68219, 59576, 51750, NA, NA, 115339, 83768, 42682, 116679, 59948, 63501, NA, 122038, 64885, 41789, 46673, 116083, 51213, NA, 67660, 49136, 37856, 95860, 78343, 84100, 99291, 87309, 81702, 93439, 38289, 44170, 42682, NA, 45383, 38289, NA, 62409, 74038, 61218, 52078, 135393, 60094, 32925, 36166, 19683, 88096, 112319, 50022, 100849, 48139, 73823, 163225, 131090, 68548, 69338, 74576, NA, 82440, 94408, 94408, 73852, 53358, 63997, 44126, 52107, NA, 44861, 47260, 48823, 52843, 54192, 47260, 77401, NA, 50439, 67660, 45852, 39369, NA, 79284, NA, 63749, NA, 38289, NA, 47260, 57318, 42682, 74576, 49019, NA, 50856, 88879, 89184, 63898, 83546, 41565, NA, NA, 41025, 21964, 42682, 45048, 42166, 37363, NA, 44170, 47260, 92358, 71015, NA, NA, NA, 94408, NA, 116679, 89641, 68499, 93342, 75706, 31848, 32925, 22094, 51273, 80503, 61681, NA, 40461, NA, 40945, 66541, 91744, 71351, 73949, 77966, 64990, 80336, 46869, 52107, 38289, 48432, 83546, 44147, NA, 76460, 62260, NA, 21964, NA, NA, 41087, 38289, NA, NA, NA, NA, NA, 44133, 36992, NA, 53984, 80301, 58752, NA, 68379, 54192, 42682, 73949, 49358, 47650, 64493, NA, NA, 49722, 43426, 41025, 41193, 41007, 47260, 48432, 44882, 39927, 40548, 56544, 49437, NA, 20140, 66171, 86129, 54661, 62632, 60399, 66104, NA, 53984, 83546, 66104, 42212, 46422, 58131, 28598, 31133, 18154, 39249, NA, 50231, 46738, 42433, NA, NA, 48849, 43000, 42979, 33993, 48198, 93076, 59688, 87873, 44489, 55964, NA, 19455, 46478, 39585, 52107, 29685, 86621, 66897, 63997, 40281, 96539, 54254, 40365, 40488, NA, NA, 42682, 41007, 57318, NA, NA, 45584, 47129, NA, NA, 66045, 115020, NA, 60161, NA, NA, NA, 53537, 55286, NA, NA, NA, 48883, NA, 46478, 198307, 87604, 70456, 76460, NA, 49652, 77715, 45383, 49832, 57995, 49929, NA, 64990, 60072, 105392, 106249, 69775, NA, 89859, 43128, NA, NA, 45500, 66653, 54435, 104749, NA, 68363, NA, 48823, 49019, 53358, NA, NA, 52107, 91744, 90348, 70776, 76460, NA, NA, 47930, 42682, 45584, NA, NA, 62012, NA, 57318, 50856, 39741, 61064, NA, 48784, 41565, 98506, 48432, 125015, 112815, 69987, 70044, 76460, NA, 41565, NA, 46762, 42682, 47553, 44189, NA, 58221, NA, 71202, 92829, 73949, 66653, NA, 58582, 54676, 48432, NA, NA, 51899, 44021, 46478, 98974, 52941, 45696, 54032, 48600, 56415, NA, NA, 48849, NA, NA, 50263, NA, 53358, 106421, 64706, 46087, NA, NA, 58522, 62012, NA, 54635, NA, 46478, 43798, 59169, 27947, NA, 22482, 24421, 95473, 111017, 66941, 98213, 147858, NA, 47260, NA, 47930, NA, NA, NA, NA, 30771, NA, 93342, 86424, 50105, 68778, 55693, 52607, 44077, 46321, 56867, 43128, 64493, 39639, NA, NA, 68666, 40737, 79473, 92543, 54697, 52941, 63997, 48823, 63005, 46087, 54852, 64493, 38289, 52941, 55964, NA, NA, 58943, 57995, 53775, NA, 67660, 31741, 58673, 50606, NA, 60399, NA, 74953, 60771, NA, 69338, 63692, 46087, 38906, 32569, 47260, 57318, 99458, 69338, NA, NA, 97907, 50231, 50439, NA, 52107, 100690, 54035, 73769, 56776, NA, NA, 52107, 44737, 57318, 41193, NA, 57017, NA, 64608, 61814, 88448, NA, 56901, 52607, 57125, 50606, 53001, 50439, 41342, 101072, 96405, 83325, 57318, NA, 67101, 43798, 50677, 78612, NA, 61218, 79284, 70009, NA, 64087, 65995, 67995, 50022, 23351, 65486, 79631, 104061, NA, 52107, 64679, 49019, 101254, 114046, 69948, 45383, 74845, 106421, NA, 63005, 57705, NA, 73272, 97367, 52107, 118650, 49840, 63997, 58673, 48432, 31851, NA, 63005, 90856, 52107, NA, 64493, 50856, 78971, 77329, 70596, 75921, 52107, 71351, 57318, 100876, 127040, 96183, NA, 88638, NA, 98847, 50856, 52107, NA, NA, 59011, 70456, NA, 76460, NA, 87604, 48198, 56931, 52107, NA, 61303, 67660, 56415, 51899, NA, 23262, 39523, 42276, 60298, 43950, 98974, 65804, 11149...
#> $ tuit_grad_res <dbl> 8130, 8130, 8130, 8130, 8130, 8130, 8130, 8130, 8130, 8130, 8130, 8130, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 11700, 11700, 9834, 9834, 9834, 9834, 6174, 6174, 6174, 6174, 6174, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 6732, 6732, 6732, 6732, 6732, 6732, 6732, 6732, 6732, 6732, 6732, 9072, 9072, 9072, 9072, 9072, 9072, 9072, 9072, 9072, 9072, 9072, 9072, 9072, 9072, 9072, 9072, 9072, 9540, 9540, 9540, 9540, 8904, 8904, 8904, 8904, 8904, 8904, 8904, 8904, 8904, 8904, 8904, 8904, 8904, 8904, 6390, 6390, 6390, 6390, 6390, 6390, 9936, 9936, 9936, 9936, 5598, 5598, 5598, 5598, 5598, 5598, 18530, 18530, 18530, 18530, 18530, 18530, 18530, 18530, 18530, 18530, 7326, 7326, 7326, 7326, 7326, 7326, 7326, 7326, 7326, 7326, 7326, 7326, 7326, 7146, 7146, 7146, 7146, 7146, 7146, 7146, 7146, 7146, 7146, 7146, 7146, 7146, 7146, 18560, 9768, 9768, 9768, 9768, 9768, 9768, 8436, 8436, 9324, 9324, 9324, 9324, 11700, 11700, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 10810, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 11372, 8956, 8956, 8956, 8956, 8956, 8956, 8956, 8956, 8956, 8956, 8956, 8956, 8956, 8956, 8956, 8956, 8956, 19680, 7680, 7680, 7680, 7680, 7680, 7680, 7680, 7680, 7680, 7379, 7379, 7379, 7379, 7379, 7379, 7379, 7379, 7379, 7379, 7379, 7379, 7379, 7379, 4626, 4626, 4626, 4626, 4626, 4626, 4626, 4626, 4626, 4626, 4626, 4626, 4626, 4626, 4626, 4626, 4932, 4932, 4932, 4932, 4932, 4932, 4932, 4932, 4932, 4770, 4770, 4594, 4594, 4594, 4594, 4594, 4594, 4594, 4594, 4594, 4594, 4594, 4594, 4594, 4594, 4594, 15678, 15678, 15678, 15678, 15678, 15678, 15678, 15678, 15678, 4716, 4716, 4716, 4716, 4716, 13152, 13152, 5022, 5022, 5022, 5022, 5022, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 10350, 10350, 10350, 10350, 10350, 10350, 10350, 10350, 10350, 10350, 10350, 19764, 19764, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 17500, 17500, 17500, 17500, 17500, 17500, 17500, 17500, 17500, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 11220, 26896, 26896, 26896, 26896, 26896, 26896, 26896, 26896, 8150, 8150, 8150, 8150, 8150, 8150, 8150, 33246, 33246, 33246, 33246, 33246, 33246, 33246, 33246, 33246, 16722, 16722, 16722, 16722, 16722, 16722, 15936, 14940, 14940, 14940, 14940, 14940, 14940, 14940, 14940, 14940, 17550, 17550, 17550, 17550, 17550, 17550, 17550, 17550, 17550, 17532, 17532, 17532, 17532, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 23580, 23580, 23580, 13320, 13320, 13320, 13320, 13320, 13320, 13320, 13320, 12888, 12888, 12888, 11280, 11280, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 32504, 32504, 32504, 32504, 32504, 32504, 32504, 10452, 10452, 10452, 10452, 10452, 10452, 10452, 10452, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 15696, 15696, 15696, 15696, 15696, 16713, 16713, 16713, 16713, 44068, 44068, 44068, 44068, 44068, 44068, 44068, 31300, 31300, 31300, 31300, 31300, 31300, 31300, 31300, 31300, 10980, 10980, 10980, 10980, 10980, 20100, 20100, 20100, 20100, 20100, 20100, 20100, 20100, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 27594, 27594, 27594, 27594, 27594, 27594, 27594, 12400, 36657, 36657, 36657, 36657, 36657, 36657, 36657, 36657, 36657, 6738, 6738, 6738, 6738, 6738, 6738, 10062, 10062, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 34680, 34680, 4410, 4410, 4410, 4410, 4410, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 6714, 9983, 9983, 9983, 9983, 9983, 9983, 9983, 9983, 9983, 9983, 9983, 10836, 10836, 10836, 10836, 10836, 10836, 10836, 10836, 10836, 10836, 10836, 10836, 10836, 10836, 10836, 10836, 12567, 12567, 12567, 12567, 15690, 15690, 15690, 15690, 15690, 15690, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 9628, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 7568, 7568, 7568, 21890, 21890, 21890, 9774, 9774, 9774, 9774, 9774, 9774, 9774, 9774, 9774, 9774, 9774, 9774, 9774, 9774, 11250, 11250, 11250, 11250, 11250, 11250, 11250, 11250, 11250, 11250, 11250, 11250, 5026, 5026, 5026, 18000, 18000, 18000, 20720, 20720, 20720, 20720, 20720, 14940, 14940, 14940, 14940, 14940, 14940, 14940, 14940, 14940, 6496, 6496, 6496, 6496, 6496, 6496, 6496, 6496, 6496, 6496, 6496, 6496, 6496, 6496, 6496, 6496, 13726, 13726, 13726, 13726, 13726, 13726, 13726, 13726, 13726, 13726, 13726, 13726, 13726, 13726, 6497, 6497, 16632, 16632, 16632, 16632, 16632, 16632, 16632, 12060, 12060, 12060, 12060, 12060, 12060, 12060, 12060, 12060, 12060, 12060, 15660, 15660, 15660, 15660, 15660, 15660, 15660, 15660, 15660, 15660, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 12822, 12822, 12822, 12822, 12822, 12822, 12822, 12822, 12822, 12822, 6497, 6497, 6497, 6497, 6497, 6497, 6497, 6497, 6497, 6497, 6497, 6497, 6497, 6497, 6497, 6497, 6497, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 5160, 5160, 30960, 30960, 30960, 30960, 30960, 30960, 30960, 30960, 30960, 30960, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 42850, 42850, 42850, 42850, 42850, 42850, 8298, 8298, 8298, 17100, 17100, 17100, 17100, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 28800, 46272, 4627...
#> $ fee_grad_res <dbl> 1236, 1236, 1236, 1236, 1236, 1236, 1236, 1236, 1236, 1236, 1236, 1236, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1390, 1390, 508, 508, 508, 508, 2284, 2284, 2284, 2284, 2284, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 640, 640, 640, 640, 640, 640, 640, 640, 640, 640, 640, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 840, 840, 840, 840, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 190, 190, 190, 190, 190, 190, 640, 640, 640, 640, 1226, 1226, 1226, 1226, 1226, 1226, 610, 610, 610, 610, 610, 610, 610, 610, 610, 610, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 1455, 1424, 1424, 1424, 1424, 1424, 1424, 1385, 1385, 1365, 1365, 1365, 1365, 410, 410, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 451, 451, 451, 451, 451, 451, 451, 451, 451, 451, 451, 451, 451, 451, 451, 451, 451, 590, 1604, 1604, 1604, 1604, 1604, 1604, 1604, 1604, 1604, 971, 971, 971, 971, 971, 971, 971, 971, 971, 971, 971, 971, 971, 971, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1026, 1026, 1026, 1026, 1026, 1026, 1026, 1026, 1026, 1530, 1530, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 500, 500, 500, 500, 500, 500, 500, 500, 500, 1192, 1192, 1192, 1192, 1192, 0, 0, 918, 918, 918, 918, 918, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 320, 320, 710, 710, 710, 710, 710, 710, 710, 710, 710, 710, 710, 710, 710, 710, 150, 150, 150, 150, 150, 150, 150, 150, 150, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 1385, 1385, 1385, 1385, 1385, 1385, 1256, 1256, 1256, 1256, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1595, 1595, 1595, 1595, 1595, 1595, 1595, 1595, 1595, 1568, 1568, 1568, 1568, 1568, 1568, 951, 951, 951, 951, 951, 951, 951, 951, 951, 951, 951, 841, 841, 841, 841, 841, 841, 841, 841, 841, 841, 841, 841, 841, 841, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1092, 1092, 1092, 1092, 1092, 1092, 1092, 1092, 1092, 1092, 1092, 1092, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 2289, 2289, 2289, 2289, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 1844, 1844, 1844, 1844, 1844, 1844, 1844, 1844, 1844, 1844, 1844, 1844, 1844, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 2118, 2118, 2118, 2118, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 2029, 2166, 2166, 370, 370, 370, 370, 370, 370, 370, 370, 0, 0, 0, 0, 0, 0, 0, 600, 600, 600, 600, 600, 600, 600, 600, 600, 300, 300, 300, 300, 300, 300, 0, 40, 40, 40, 40, 40, 40, 40, 40, 40, 85, 85, 85, 85, 85, 85, 85, 85, 85, 500, 500, 500, 500, 1737, 1737, 1737, 1737, 1737, 1737, 1737, 1737, 348, 348, 348, 180, 180, 180, 180, 180, 180, 180, 180, 930, 930, 930, 0, 0, 310, 310, 310, 310, 310, 310, 310, 310, 310, 310, 310, 310, 310, 310, 310, 310, 1148, 1148, 1148, 1148, 1148, 1148, 1148, 135, 135, 135, 135, 135, 135, 135, 135, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 80, 80, 80, 80, 80, 619, 619, 619, 619, 380, 380, 380, 380, 380, 380, 380, 120, 120, 120, 120, 120, 120, 120, 120, 120, 0, 0, 0, 0, 0, 172, 172, 172, 172, 172, 172, 172, 172, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 1946, 1946, 1946, 1946, 1946, 1946, 1946, 1946, 1946, 1946, 1946, 1946, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1916, 1916, 1916, 1916, 1916, 1916, 0, 0, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 400, 400, 2488, 2488, 2488, 2488, 2488, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 840, 840, 840, 840, 2152, 2152, 2152, 2152, 2152, 2152, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 1073, 1073, 1073, 670, 670, 670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1350, 1350, 1350, 2000, 2000, 2000, 184, 184, 184, 184, 184, 2510, 2510, 2510, 2510, 2510, 2510, 2510, 2510, 2510, 4460, 4460, 4460, 4460, 4460, 4460, 4460, 4460, 4460, 4460, 4460, 4460, 4460, 4460, 4460, 4460, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 5284, 5284, 80, 80, 80, 80, 80, 80, 80, 510, 510, 510, 510, 510, 510, 510, 510, 510, 510, 510, 200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 720, 720, 720, 720, 720, 720, 720, 720, 720, 720, 720, 720, 720, 720, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 828, 828, 828, 828, 828, 828, 828, 828, 828, 828, 4722, 4722, 4722, 4722, 4722, 4722, 4722, 4722, 4722, 4722, 4722, 4722, 4722, 4722, 4801, 4801, 4801, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 350, 350, 792, 792, 792, 792, 792, 792, 792, 792, 792, 792, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 600, 600, 600, 600, 600, 600, 860, 860, 860, 526, 526, 526, 526, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 450, 1489, 1489, 1489, 1489, 1489, 1489, 1489, 1489, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 100, 100, 100, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1956, 1294, 1294, 1294, 1294, 1294, 1294, 1294, 1294, 1857, 1857, 1857, 1857, 1857, 1857, 1857, 1857, 1857, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 1190, 250, 250, 250, 250, 250, 250, 250, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 2185, 200, 200, 200, 200, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1859, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 1967, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1016, 1797, 1797, 1797, 1797, 1797, 1797, 1797, 1797, 1797, 1797, 1797, 1797, 1797, 1797, 1797, 1797, 1797, 1797, 1797, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 400, 400, 400, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, 2078, ...
#> $ tuit_grad_nres <dbl> 16260, 16260, 16260, 16260, 16260, 16260, 16260, 16260, 16260, 16260, 16260, 16260, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 11700, 11700, 21830, 21830, 21830, 21830, 12348, 12348, 12348, 12348, 12348, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 15138, 15138, 15138, 15138, 15138, 15138, 15138, 15138, 15138, 15138, 15138, 27216, 27216, 27216, 27216, 27216, 27216, 27216, 27216, 27216, 27216, 27216, 27216, 27216, 27216, 27216, 27216, 27216, 9540, 9540, 9540, 9540, 17808, 17808, 17808, 17808, 17808, 17808, 17808, 17808, 17808, 17808, 17808, 17808, 17808, 17808, 12780, 12780, 12780, 12780, 12780, 12780, 20592, 20592, 20592, 20592, 11196, 11196, 11196, 11196, 11196, 11196, 18530, 18530, 18530, 18530, 18530, 18530, 18530, 18530, 18530, 18530, 14652, 14652, 14652, 14652, 14652, 14652, 14652, 14652, 14652, 14652, 14652, 14652, 14652, 14292, 14292, 14292, 14292, 14292, 14292, 14292, 14292, 14292, 14292, 14292, 14292, 14292, 14292, 18560, 19954, 19954, 19954, 19954, 19954, 19954, 17233, 17233, 19047, 19047, 19047, 19047, 11700, 11700, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 23480, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 31124, 17781, 17781, 17781, 17781, 17781, 17781, 17781, 17781, 17781, 17781, 17781, 17781, 17781, 17781, 17781, 17781, 17781, 19680, 17400, 17400, 17400, 17400, 17400, 17400, 17400, 17400, 17400, 18842, 18842, 18842, 18842, 18842, 18842, 18842, 18842, 18842, 18842, 18842, 18842, 18842, 18842, 9252, 9252, 9252, 9252, 9252, 9252, 9252, 9252, 9252, 9252, 9252, 9252, 9252, 9252, 9252, 9252, 9864, 9864, 9864, 9864, 9864, 9864, 9864, 9864, 9864, 9180, 9180, 9188, 9188, 9188, 9188, 9188, 9188, 9188, 9188, 9188, 9188, 9188, 9188, 9188, 9188, 9188, 15678, 15678, 15678, 15678, 15678, 15678, 15678, 15678, 15678, 9666, 9666, 9666, 9666, 9666, 13152, 13152, 7452, 7452, 7452, 7452, 7452, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 16224, 10350, 10350, 10350, 10350, 10350, 10350, 10350, 10350, 10350, 10350, 10350, 19764, 19764, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 11430, 17500, 17500, 17500, 17500, 17500, 17500, 17500, 17500, 17500, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26322, 26896, 26896, 26896, 26896, 26896, 26896, 26896, 26896, 8150, 8150, 8150, 8150, 8150, 8150, 8150, 33246, 33246, 33246, 33246, 33246, 33246, 33246, 33246, 33246, 16722, 16722, 16722, 16722, 16722, 16722, 15936, 14940, 14940, 14940, 14940, 14940, 14940, 14940, 14940, 14940, 17550, 17550, 17550, 17550, 17550, 17550, 17550, 17550, 17550, 17532, 17532, 17532, 17532, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 23580, 23580, 23580, 13320, 13320, 13320, 13320, 13320, 13320, 13320, 13320, 12888, 12888, 12888, 11280, 11280, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 19755, 32504, 32504, 32504, 32504, 32504, 32504, 32504, 10452, 10452, 10452, 10452, 10452, 10452, 10452, 10452, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 11232, 15696, 15696, 15696, 15696, 15696, 16713, 16713, 16713, 16713, 44068, 44068, 44068, 44068, 44068, 44068, 44068, 31300, 31300, 31300, 31300, 31300, 31300, 31300, 31300, 31300, 10980, 10980, 10980, 10980, 10980, 20100, 20100, 20100, 20100, 20100, 20100, 20100, 20100, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 25470, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 23310, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 27594, 27594, 27594, 27594, 27594, 27594, 27594, 12400, 36657, 36657, 36657, 36657, 36657, 36657, 36657, 36657, 36657, 15666, 15666, 15666, 15666, 15666, 15666, 10062, 10062, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 41592, 34680, 34680, 10332, 10332, 10332, 10332, 10332, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 22374, 20153, 20153, 20153, 20153, 20153, 20153, 20153, 20153, 20153, 20153, 20153, 28656, 28656, 28656, 28656, 28656, 28656, 28656, 28656, 28656, 28656, 28656, 28656, 28656, 28656, 28656, 28656, 12567, 12567, 12567, 12567, 34020, 34020, 34020, 34020, 34020, 34020, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 23604, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 45288, 11873, 11873, 11873, 21890, 21890, 21890, 19068, 19068, 19068, 19068, 19068, 19068, 19068, 19068, 19068, 19068, 19068, 19068, 19068, 19068, 11250, 11250, 11250, 11250, 11250, 11250, 11250, 11250, 11250, 11250, 11250, 11250, 14942, 14942, 14942, 18000, 18000, 18000, 20720, 20720, 20720, 20720, 20720, 14940, 14940, 14940, 14940, 14940, 14940, 14940, 14940, 14940, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 34762, 34762, 34762, 34762, 34762, 34762, 34762, 34762, 34762, 34762, 34762, 34762, 34762, 34762, 18102, 18102, 16632, 16632, 16632, 16632, 16632, 16632, 16632, 12060, 12060, 12060, 12060, 12060, 12060, 12060, 12060, 12060, 12060, 12060, 15660, 15660, 15660, 15660, 15660, 15660, 15660, 15660, 15660, 15660, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 17730, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 20745, 12822, 12822, 12822, 12822, 12822, 12822, 12822, 12822, 12822, 12822, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 18102, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 39800, 11376, 11376, 30960, 30960, 30960, 30960, 30960, 30960, 30960, 30960, 30960, 30960, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 8190, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 28422, 2842...
#> $ fee_grad_nres <dbl> 1236, 1236, 1236, 1236, 1236, 1236, 1236, 1236, 1236, 1236, 1236, 1236, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1390, 1390, 508, 508, 508, 508, 2284, 2284, 2284, 2284, 2284, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 640, 640, 640, 640, 640, 640, 640, 640, 640, 640, 640, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 1624, 840, 840, 840, 840, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 190, 190, 190, 190, 190, 190, 640, 640, 640, 640, 1226, 1226, 1226, 1226, 1226, 1226, 610, 610, 610, 610, 610, 610, 610, 610, 610, 610, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 802, 1455, 1758, 1758, 1758, 1758, 1758, 1758, 1727, 1727, 1743, 1743, 1743, 1743, 410, 410, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 1011, 513, 513, 513, 513, 513, 513, 513, 513, 513, 513, 513, 513, 513, 513, 513, 513, 513, 590, 1604, 1604, 1604, 1604, 1604, 1604, 1604, 1604, 1604, 971, 971, 971, 971, 971, 971, 971, 971, 971, 971, 971, 971, 971, 971, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1292, 1026, 1026, 1026, 1026, 1026, 1026, 1026, 1026, 1026, 1530, 1530, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 1287, 500, 500, 500, 500, 500, 500, 500, 500, 500, 1192, 1192, 1192, 1192, 1192, 0, 0, 918, 918, 918, 918, 918, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 220, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 320, 320, 710, 710, 710, 710, 710, 710, 710, 710, 710, 710, 710, 710, 710, 710, 150, 150, 150, 150, 150, 150, 150, 150, 150, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 3603, 1385, 1385, 1385, 1385, 1385, 1385, 1256, 1256, 1256, 1256, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1138, 1595, 1595, 1595, 1595, 1595, 1595, 1595, 1595, 1595, 1568, 1568, 1568, 1568, 1568, 1568, 951, 951, 951, 951, 951, 951, 951, 951, 951, 951, 951, 841, 841, 841, 841, 841, 841, 841, 841, 841, 841, 841, 841, 841, 841, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1088, 1092, 1092, 1092, 1092, 1092, 1092, 1092, 1092, 1092, 1092, 1092, 1092, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 988, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 911, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1115, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 1428, 2289, 2289, 2289, 2289, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 1844, 1844, 1844, 1844, 1844, 1844, 1844, 1844, 1844, 1844, 1844, 1844, 1844, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 1463, 2118, 2118, 2118, 2118, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 1865, 2029, 2166, 2166, 370, 370, 370, 370, 370, 370, 370, 370, 0, 0, 0, 0, 0, 0, 0, 600, 600, 600, 600, 600, 600, 600, 600, 600, 300, 300, 300, 300, 300, 300, 0, 40, 40, 40, 40, 40, 40, 40, 40, 40, 85, 85, 85, 85, 85, 85, 85, 85, 85, 500, 500, 500, 500, 1737, 1737, 1737, 1737, 1737, 1737, 1737, 1737, 348, 348, 348, 180, 180, 180, 180, 180, 180, 180, 180, 930, 930, 930, 0, 0, 310, 310, 310, 310, 310, 310, 310, 310, 310, 310, 310, 310, 310, 310, 310, 310, 1148, 1148, 1148, 1148, 1148, 1148, 1148, 135, 135, 135, 135, 135, 135, 135, 135, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 80, 80, 80, 80, 80, 619, 619, 619, 619, 380, 380, 380, 380, 380, 380, 380, 120, 120, 120, 120, 120, 120, 120, 120, 120, 0, 0, 0, 0, 0, 172, 172, 172, 172, 172, 172, 172, 172, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 1612, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 354, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 1012, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 1946, 1946, 1946, 1946, 1946, 1946, 1946, 1946, 1946, 1946, 1946, 1946, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1916, 1916, 1916, 1916, 1916, 1916, 0, 0, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 713, 400, 400, 2488, 2488, 2488, 2488, 2488, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 1738, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 1774, 840, 840, 840, 840, 2152, 2152, 2152, 2152, 2152, 2152, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 2088, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 303, 1073, 1073, 1073, 670, 670, 670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 1670, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1350, 1350, 1350, 2000, 2000, 2000, 184, 184, 184, 184, 184, 2510, 2510, 2510, 2510, 2510, 2510, 2510, 2510, 2510, 5654, 5654, 5654, 5654, 5654, 5654, 5654, 5654, 5654, 5654, 5654, 5654, 5654, 5654, 5654, 5654, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 2270, 6479, 6479, 80, 80, 80, 80, 80, 80, 80, 510, 510, 510, 510, 510, 510, 510, 510, 510, 510, 510, 200, 200, 200, 200, 200, 200, 200, 200, 200, 200, 720, 720, 720, 720, 720, 720, 720, 720, 720, 720, 720, 720, 720, 720, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 828, 828, 828, 828, 828, 828, 828, 828, 828, 828, 5917, 5917, 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#> $ books_supplies <dbl> 1600, 1600, 1600, 1600, 1600, 1600, 1600, 1600, 1600, 1600, 1600, 1600, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1500, 1500, 1688, 1688, 1688, 1688, 1600, 1600, 1600, 1600, 1600, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1100, 1100, 1100, 1100, 1100, 1100, 1100, 1100, 1100, 1100, 1100, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1200, 1800, 1800, 1800, 1800, 1596, 1596, 1596, 1596, 1596, 1596, 1596, 1596, 1596, 1596, 1596, 1596, 1596, 1596, 1200, 1200, 1200, 1200, 1200, 1200, 1020, 1020, 1020, 1020, 1500, 1500, 1500, 1500, 1500, 1500, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1000, 1260, 1260, 1260, 1260, 1260, 1260, 1260, 1260, 1260, 1260, 1260, 1260, 1260, 1129, 1129, 1129, 1129, 1129, 1129, 1129, 1129, 1129, 1129, 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#> $ roomboard_off <dbl> 8830, 8830, 8830, 8830, 8830, 8830, 8830, 8830, 8830, 8830, 8830, 8830, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 11682, 9600, 9600, 9603, 9603, 9603, 9603, 7320, 7320, 7320, 7320, 7320, 13050, 13050, 13050, 13050, 13050, 13050, 13050, 13050, 13050, 13050, 13050, 13050, 13050, 13050, 13050, 13050, 13050, 13050, 13050, 13050, 9657, 9657, 9657, 9657, 9657, 9657, 9657, 9657, 9657, 9657, 9657, 12898, 12898, 12898, 12898, 12898, 12898, 12898, 12898, 12898, 12898, 12898, 12898, 12898, 12898, 12898, 12898, 12898, 8000, 8000, 8000, 8000, 9296, 9296, 9296, 9296, 9296, 9296, 9296, 9296, 9296, 9296, 9296, 9296, 9296, 9296, 7122, 7122, 7122, 7122, 7122, 7122, 8980, 8980, 8980, 8980, 7284, 7284, 7284, 7284, 7284, 7284, 9850, 9850, 9850, 9850, 9850, 9850, 9850, 9850, 9850, 9850, 8591, 8591, 8591, 8591, 8591, 8591, 8591, 8591, 8591, 8591, 8591, 8591, 8591, 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#> $ oth_expense_off <dbl> 3090, 3090, 3090, 3090, 3090, 3090, 3090, 3090, 3090, 3090, 3090, 3090, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 4886, 1600, 1600, 3578, 3578, 3578, 3578, 4228, 4228, 4228, 4228, 4228, 4116, 4116, 4116, 4116, 4116, 4116, 4116, 4116, 4116, 4116, 4116, 4116, 4116, 4116, 4116, 4116, 4116, 4116, 4116, 4116, 3690, 3690, 3690, 3690, 3690, 3690, 3690, 3690, 3690, 3690, 3690, 5664, 5664, 5664, 5664, 5664, 5664, 5664, 5664, 5664, 5664, 5664, 5664, 5664, 5664, 5664, 5664, 5664, 4700, 4700, 4700, 4700, 7416, 7416, 7416, 7416, 7416, 7416, 7416, 7416, 7416, 7416, 7416, 7416, 7416, 7416, 3006, 3006, 3006, 3006, 3006, 3006, 3180, 3180, 3180, 3180, 2800, 2800, 2800, 2800, 2800, 2800, 5498, 5498, 5498, 5498, 5498, 5498, 5498, 5498, 5498, 5498, 4150, 4150, 4150, 4150, 4150, 4150, 4150, 4150, 4150, 4150, 4150, 4150, 4150, 5227, 5227, 5227, 5227, 5227, 5227, 5227, 5227, 5227, 5227, 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5354, ...
#> $ tuitfee_grad_res <dbl> 9366, 9366, 9366, 9366, 9366, 9366, 9366, 9366, 9366, 9366, 9366, 9366, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 7588, 13090, 13090, 10342, 10342, 10342, 10342, 8458, 8458, 8458, 8458, 8458, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 10470, 7372, 7372, 7372, 7372, 7372, 7372, 7372, 7372, 7372, 7372, 7372, 10696, 10696, 10696, 10696, 10696, 10696, 10696, 10696, 10696, 10696, 10696, 10696, 10696, 10696, 10696, 10696, 10696, 10380, 10380, 10380, 10380, 9204, 9204, 9204, 9204, 9204, 9204, 9204, 9204, 9204, 9204, 9204, 9204, 9204, 9204, 6580, 6580, 6580, 6580, 6580, 6580, 10576, 10576, 10576, 10576, 6824, 6824, 6824, 6824, 6824, 6824, 19140, 19140, 19140, 19140, 19140, 19140, 19140, 19140, 19140, 19140, 7326, 7326, 7326, 7326, 7326, 7326, 7326, 7326, 7326, 7326, 7326, 7326, 7326, 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28845, ...
#> $ tuitfee_grad_nres <dbl> 17496, 17496, 17496, 17496, 17496, 17496, 17496, 17496, 17496, 17496, 17496, 17496, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 17294, 13090, 13090, 22338, 22338, 22338, 22338, 14632, 14632, 14632, 14632, 14632, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 26950, 15778, 15778, 15778, 15778, 15778, 15778, 15778, 15778, 15778, 15778, 15778, 28840, 28840, 28840, 28840, 28840, 28840, 28840, 28840, 28840, 28840, 28840, 28840, 28840, 28840, 28840, 28840, 28840, 10380, 10380, 10380, 10380, 18108, 18108, 18108, 18108, 18108, 18108, 18108, 18108, 18108, 18108, 18108, 18108, 18108, 18108, 12970, 12970, 12970, 12970, 12970, 12970, 21232, 21232, 21232, 21232, 12422, 12422, 12422, 12422, 12422, 12422, 19140, 19140, 19140, 19140, 19140, 19140, 19140, 19140, 19140, 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#> $ coa_grad_nres <dbl> 31016, 31016, 31016, 31016, 31016, 31016, 31016, 31016, 31016, 31016, 31016, 31016, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 35062, 25790, 25790, 37207, 37207, 37207, 37207, 27780, 27780, 27780, 27780, 27780, 45316, 45316, 45316, 45316, 45316, 45316, 45316, 45316, 45316, 45316, 45316, 45316, 45316, 45316, 45316, 45316, 45316, 45316, 45316, 45316, 30225, 30225, 30225, 30225, 30225, 30225, 30225, 30225, 30225, 30225, 30225, 48602, 48602, 48602, 48602, 48602, 48602, 48602, 48602, 48602, 48602, 48602, 48602, 48602, 48602, 48602, 48602, 48602, 24880, 24880, 24880, 24880, 36416, 36416, 36416, 36416, 36416, 36416, 36416, 36416, 36416, 36416, 36416, 36416, 36416, 36416, 24298, 24298, 24298, 24298, 24298, 24298, 34412, 34412, 34412, 34412, 24006, 24006, 24006, 24006, 24006, 24006, 35488, 35488, 35488, 35488, 35488, 35488, 35488, 35488, 35488, 35488, 28653, 28653, 28653, 28653, 28653, 28653, 28653, 28653, 28653, 28653, 28653, 28653, 28653, 27265, 27265, 27265, 27265, 27265, 27265, 27265, 27265, 27265, 27265, 27265, 27265, 27265, 27265, 36673, 42616, 42616, 42616, 42616, 42616, 42616, 36690, 36690, 36775, 36775, 36775, 36775, 32550, 32550, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 39203, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 49435, 33626, 33626, 33626, 33626, 33626, 33626, 33626, 33626, 33626, 33626, 33626, 33626, 33626, 33626, 33626, 33626, 33626, 28048, 35338, 35338, 35338, 35338, 35338, 35338, 35338, 35338, 35338, 35295, 35295, 35295, 35295, 35295, 35295, 35295, 35295, 35295, 35295, 35295, 35295, 35295, 35295, 25793, 25793, 25793, 25793, 25793, 25793, 25793, 25793, 25793, 25793, 25793, 25793, 25793, 25793, 25793, 25793, 29700, 29700, 29700, 29700, 29700, 29700, 29700, 29700, 29700, 23610, 23610, 24200, 24200, 24200, 24200, 24200, 24200, 24200, 24200, 24200, 24200, 24200, 24200, 24200, 24200, 24200, 26548, 26548, 26548, 26548, 26548, 26548, 26548, 26548, 26548, 25068, 25068, 25068, 25068, 25068, 19302, 19302, 23824, 23824, 23824, 23824, 23824, 34888, 34888, 34888, 34888, 34888, 34888, 34888, 34888, 34888, 34888, 34888, 34888, 34888, 34888, 34888, 34888, 25896, 25896, 25896, 25896, 25896, 25896, 25896, 25896, 25896, 25896, 25896, NA, NA, 30458, 30458, 30458, 30458, 30458, 30458, 30458, 30458, 30458, 30458, 30458, 30458, 30458, 30458, 36191, 36191, 36191, 36191, 36191, 36191, 36191, 36191, 36191, 36270, 36270, 36270, 36270, 36270, 36270, 36270, 36270, 36270, 36270, 36270, 36270, 36270, 36270, 36270, 35653, 35653, 35653, 35653, 35653, 35653, 31838, 31838, 31838, 31838, 35023, 35023, 35023, 35023, 35023, 35023, 35023, 35023, 35023, 35023, 35023, 35023, 35023, 35023, 35023, 34215, 34215, 34215, 34215, 34215, 34215, 34215, 34215, 34215, 32864, 32864, 32864, 32864, 32864, 32864, 34139, 34139, 34139, 34139, 34139, 34139, 34139, 34139, 34139, 34139, 34139, 33449, 33449, 33449, 33449, 33449, 33449, 33449, 33449, 33449, 33449, 33449, 33449, 33449, 33449, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 35458, 34848, 34848, 34848, 34848, 34848, 34848, 34848, 34848, 34848, 34848, 34848, 34848, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 34396, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 35281, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 31921, 34036, 34036, 34036, 34036, 34036, 34036, 34036, 34036, 34036, 34036, 34036, 34036, 34036, 34036, 34036, 34036, 34036, 34036, 34036, 34036, 45575, 45575, 45575, 45575, 44211, 44211, 44211, 44211, 44211, 44211, 44211, 44211, 44211, 44211, 45129, 45129, 45129, 45129, 45129, 45129, 45129, 45129, 45129, 45129, 45129, 45129, 45129, 45228, 45228, 45228, 45228, 45228, 45228, 45228, 45228, 45228, 45228, 45228, 45228, 45228, 45228, 45228, 45228, 45228, 45228, 45228, 44481, 44481, 44481, 44481, 45480, 45480, 45480, 45480, 45480, 45480, 45480, 45480, 45480, 45480, 45480, 45480, 45480, 45480, 45742, 46226, 46226, 45134, 45134, 45134, 45134, 45134, 45134, 45134, 45134, 26590, 26590, 26590, 26590, 26590, 26590, 26590, NA, NA, NA, NA, NA, NA, NA, NA, NA, 28066, 28066, 28066, 28066, 28066, 28066, NA, 34366, 34366, 34366, 34366, 34366, 34366, 34366, 34366, 34366, 37365, 37365, 37365, 37365, 37365, 37365, 37365, 37365, 37365, 37616, 37616, 37616, 37616, 34145, 34145, 34145, 34145, 34145, 34145, 34145, 34145, NA, NA, NA, 32041, 32041, 32041, 32041, 32041, 32041, 32041, 32041, 32637, 32637, 32637, 28479, 28479, 38506, 38506, 38506, 38506, 38506, 38506, 38506, 38506, 38506, 38506, 38506, 38506, 38506, 38506, 38506, 38506, 50948, 50948, 50948, 50948, 50948, 50948, 50948, 30167, 30167, 30167, 30167, 30167, 30167, 30167, 30167, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 27624, 35450, 35450, 35450, 35450, 35450, 35860, 35860, 35860, 35860, 62889, 62889, 62889, 62889, 62889, 62889, 62889, 49750, 49750, 49750, 49750, 49750, 49750, 49750, 49750, 49750, 29420, 29420, 29420, 29420, 29420, 38695, 38695, 38695, 38695, 38695, 38695, 38695, 38695, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 34442, 44274, 44274, 44274, 44274, 44274, 44274, 44274, 44274, 44274, 44274, 44274, 44274, 44274, 44274, 44274, 44274, 44274, 44274, 35426, 35426, 35426, 35426, 35426, 35426, 35426, 35426, 35426, 35426, 35426, 35426, 35426, 35426, 35426, 35426, 35426, 35426, 35426, 35426, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 42750, 36318, 36318, 36318, 36318, 36318, 36318, 36318, 36318, 36318, 36318, 36318, 36318, 46035, 46035, 46035, 46035, 46035, 46035, 46035, 28988, 53174, 53174, 53174, 53174, 53174, 53174, 53174, 53174, 53174, 36178, 36178, 36178, 36178, 36178, 36178, 20472, 20472, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 59733, 53530, 53530, 27076, 27076, 27076, 27076, 27076, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 42310, 36953, 36953, 36953, 36953, 36953, 36953, 36953, 36953, 36953, 36953, 36953, 46312, 46312, 46312, 46312, 46312, 46312, 46312, 46312, 46312, 46312, 46312, 46312, 46312, 46312, 46312, 46312, 24917, 24917, 24917, 24917, 49354, 49354, 49354, 49354, 49354, 49354, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 37945, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 61446, 30004, 30004, 30004, 40666, 40666, 40666, 34992, 34992, 34992, 34992, 34992, 34992, 34992, 34992, 34992, 34992, 34992, 34992, 34992, 34992, 26016, 26016, 26016, 26016, 26016, 26016, 26016, 26016, 26016, 26016, 26016, 26016, 31465, 31465, 31465, 33756, 33756, 33756, 40945, 40945, 40945, 40945, 40945, 37678, 37678, 37678, 37678, 37678, 37678, 37678, 37678, 37678, 39230, 39230, 39230, 39230, 39230, 39230, 39230, 39230, 39230, 39230, 39230, 39230, 39230, 39230, 39230, 39230, 52968, 52968, 52968, 52968, 52968, 52968, 52968, 52968, 52968, 52968, 52968, 52968, 52968, 52968, 37534, 37534, 33452, 33452, 33452, 33452, 33452, 33452, 33452, 28334, 28334, 28334, 28334, 28334, 28334, 28334, 28334, 28334, 28334, 28334, 31088, 31088, 31088, 31088, 31088, 31088, 31088, 31088, 31088, 31088, 35600, 35600, 35600, 35600, 35600, 35600, 35600, 35600, 35600, 35600, 35600, 35600, 35600, 35600, 35557, 35557, 35557, 35557, 35557, 35557, 35557, 35557, 35557, 35557, 35557, 35557, 35557, 35557, 28044, 28044, 28044, 28044, 28044, 28044, 28044, 28044, 28044, 28044, 39089, 39089, 39089, 39089, 39089, 39089, 39089, 39089, 39089, 39089, 39089, 39089, 39089, 39089, 40202, 40202, 40202, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 31393, 31393, 46120, 46120, 46120, 46120, 46120, 46120, 46120, 46120, 46120, 46120, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 17840, 46531, 46531, 46531, 46531, 46531, 46531, 46531, 46531, 46531, 46531, 4...
rm(df_ipeds_pop) # comment this line out if you want to keep ipeds data frame
rm(df_scorecard) # comment this line out if you want to keep scorecard data frame
# Investigate analysis data frame `df_score_ipeds`
# data structure: variables that uniquely identify obs
df_score_ipeds %>% group_by(opeid6,cipcode) %>% summarise(n_per_key=n()) %>% ungroup() %>% count(n_per_key)
#> # A tibble: 1 x 2
#> n_per_key n
#> <int> <int>
#> 1 1 9444
# number of observations (universities) for each 4-digit cip code (degree code)
#df_score_ipeds %>% count(cipcode)
df_score_ipeds %>% filter(cipcode=='4407') %>% count(cipcode) # social work
#> # A tibble: 1 x 2
#> cipcode n
#> <chr> <int>
#> 1 4407 257
##### create data frame that only contains observations for MAs in social work;
#filter(cipcode=='4407')
df_socialwork <- df_score_ipeds %>%
filter(cipcode=='4407') %>%
# remove observations with missing values of cost of attendance (better for teaching concepts)
filter(!is.na(coa_grad_res))
df_socialwork %>% glimpse()
#> Rows: 253
#> Columns: 36
#> $ opeid6 <chr> "001002", "001005", "001051", "001036", "001047", "011462", "001081", "001101", "001108", "001090", "001117", "007993", "001157", "001142", "001146", "001141", "001147", "001137", "001138", "001139", "001140", "001153", "001150", "001315", "001149", "001151", "001154", "001155", "001328", "001350", "001371", "001360", "001417", "001402", "001409", "001406", "001428", "001443", "001466", "003954", "001480", "009635", "001489", "001509", "001526", "001537", "003955", "001544", "001574", "001598", "001590", "001599", "001610", "007279", "001616", "001624", "001634", "001694", "001671", "009145", "001776", "001692", "001710", "001693", "001750", "001664", "001758", "001759", "001813", "001816", "001815", "001811", "001892", "001890", "001889", "001948", "001939", "001949", "001950", "001952", "001959", "001989", "001999", "009275", "001960", "002002", "002006", "002010", "002026", "002029", "002053", "002050", "002054", "002083", "002091", "002128", "002130", "002183", "002188", "002208", "002211", "002189", "002238", "002259", "002260", "002268", "002282", "002325", "002290", "002329", "002330", "002334", "002360", "003969", "002388", "002377", "002343", "002345", "002410", "002424", "002441", "002516", "002518", "002519", "002498", "002506", "002503", "002520", "002536", "002554", "002569", "002568", "002589", "002622", "002616", "002617", "009344", "002629", "002632", "009345", "002657", "002664", "002666", "002707", "002698", "002689", "007022", "002808", "002722", "002744", "002751", "002779", "002785", "002805", "002835", "002836", "002837", "002838", "002882", "010142", "002903", "002906", "002923", "002928", "002905", "002974", "002975", "002976", "002950", "002972", "002984", "002954", "002981", "003005", "003123", "003024", "003125", "003032", "003077", "003090", "003100", "003131", "003078", "003145", "003184", "003194", "003212", "003216", "003316", "003321", "003322", "003296", "003325", "003378", "003326", "003371", "003328", "003313", "003407", "003448", "003456", "003474", "003478", "003487", "003509", "003510", "003518", "003529", "003530", "003522", "003528", "003537", "003545", "003565", "003652", "003598", "003599", "003624", "003615", "003631", "003656", "003658", "003661", "003636", "010115", "003644", "003665", "003670", "003677", "003675", "003696", "003749", "003765", "003732", "003735", "003775", "003790", "003799", "003798", "003810", "003815", "003827", "003899", "003920", "003895", "003896", "003932", "005026", "007108", "011719", "030113", "032603", "032553"
#> $ unitid <dbl> 100654, 100724, 100751, 102049, 102368, 102553, 104151, 106245, 106397, 106458, 109785, 110486, 110495, 110510, 110538, 110547, 110556, 110565, 110574, 110583, 110592, 110608, 110617, 110662, 115755, 122409, 122597, 122755, 123961, 126818, 127060, 127565, 129020, 130226, 130314, 130493, 130934, 131450, 132471, 132903, 133650, 133951, 134097, 136215, 137032, 137351, 138354, 138716, 139940, 139959, 140960, 141264, 141574, 141644, 142115, 142461, 143118, 144005, 144740, 145336, 145600, 145813, 146719, 147776, 148496, 148584, 149222, 149231, 151111, 151342, 151360, 151388, 153658, 154095, 154235, 155317, 155335, 156082, 156125, 156213, 156365, 157085, 157289, 157447, 157757, 157951, 159009, 159391, 160630, 160755, 161253, 161457, 161554, 163453, 163851, 164924, 164988, 165024, 167729, 167783, 167899, 168263, 168740, 169798, 169910, 170082, 170806, 170976, 171100, 172644, 172699, 173045, 173920, 174066, 174233, 174783, 174899, 174914, 175856, 176044, 176372, 178396, 178402, 178420, 178721, 179159, 179566, 179867, 180489, 181394, 182281, 182290, 183044, 185262, 185572, 185590, 186201, 186380, 186584, 186876, 188030, 188304, 188429, 190150, 190558, 190594, 190637, 190725, 191241, 192192, 192448, 193584, 193900, 194958, 196060, 196079, 196088, 196097, 196413, 196592, 197708, 197869, 198464, 198543, 199102, 199120, 199139, 199148, 199157, 199193, 199218, 199281, 200004, 200280, 200800, 201645, 201885, 202134, 204024, 204796, 204857, 206084, 206604, 206695, 207500, 208822, 209612, 209807, 211361, 212160, 213349, 213826, 214041, 215062, 216010, 216339, 216764, 216852, 217420, 218663, 218964, 219471, 219602, 220075, 220862, 220978, 221661, 221740, 221759, 221838, 221971, 222178, 223232, 224554, 225511, 227331, 227368, 228431, 228459, 228529, 228769, 228778, 228796, 228875, 229027, 229115, 229814, 230038, 230728, 230764, 231174, 232186, 232937, 233277, 234030, 235097, 236595, 236896, 236948, 237330, 237525, 238032, 240277, 240365, 240444, 240453, 240727, 242635, 243221, 243601, 366711, 409698, 433660
#> $ instnm <chr> "Alabama A & M University", "Alabama State University", "The University of Alabama", "Samford University", "Troy University", "University of Alaska Anchorage", "Arizona State University-Tempe", "University of Arkansas at Little Rock", "University of Arkansas", "Arkansas State University-Main Campus", "Azusa Pacific University", "California State University-Bakersfield", "California State University-Stanislaus", "California State University-San Bernardino", "California State University-Chico", "California State University-Dominguez Hills", "California State University-Fresno", "California State University-Fullerton", "California State University-East Bay", "California State University-Long Beach", "California State University-Los Angeles", "California State University-Northridge", "California State University-Sacramento", "University of California-Los Angeles", "Humboldt State University", "San Diego State University", "San Francisco State University", "San Jose State University", "University of Southern California", "Colorado State University-Fort Collins", "University of Denver", "Metropolitan State University of Denver", "University of Connecticut", "Quinnipiac University", "University of Saint Joseph", "Southern Connecticut State University", "Delaware State University", "Gallaudet University", "Barry University", "University of Central Florida", "Florida Agricultural and Mechanical University", "Florida International University", "Florida State University", "Nova Southeastern University", "Saint Leo University", "University of South Florida-Main Campus", "The University of West Florida", "Albany State University", "Georgia State University", "University of Georgia", "Savannah State University", "Valdosta State University", "University of Hawaii at Manoa", "Hawaii Pacific University", "Boise State University", "Northwest Nazarene University", "Aurora University", "Chicago State University", "DePaul University", "Governors State University", "University of Illinois at Chicago", "Illinois State University", "Loyola University Chicago", "Northeastern Illinois University", "Dominican University", "University of St Francis", "Southern Illinois University-Carbondale", "Southern Illinois University-Edwardsville", "Indiana University-Purdue University-Indianapolis", "Indiana University-South Bend", "Indiana University-Northwest", "Indiana University-East", "University of Iowa", "University of Northern Iowa", "Saint Ambrose University", "University of Kansas", "Newman University", "Washburn University", "Wichita State University", "Asbury University", "Campbellsville University", "University of Kentucky", "University of Louisville", "Northern Kentucky University", "Spalding University", "Western Kentucky University", "Grambling State University", "Louisiana State University and Agricultural & Mechanical College", "Southern University at New Orleans", "Tulane University of Louisiana", "University of Maine", "University of New England", "University of Southern Maine", "Morgan State University", "Salisbury University", "Boston College", "Boston University", "Bridgewater State University", "Salem State University", "Simmons University", "Springfield College", "Westfield State University", "Andrews University", "Eastern Michigan University", "Ferris State University", "Grand Valley State University", "Madonna University", "University of Michigan-Ann Arbor", "Michigan State University", "Wayne State University", "Western Michigan University", "Augsburg University", "Minnesota State University-Mankato", "University of Minnesota-Twin Cities", "University of Minnesota-Duluth", "Saint Cloud State University", "The College of Saint Scholastica", "University of St Thomas", "Jackson State University", "Mississippi Valley State University", "University of Southern Mississippi", "University of Missouri-Columbia", "University of Missouri-Kansas City", "University of Missouri-St Louis", "Park University", "Saint Louis University", "Missouri State University-Springfield", "Washington University in St Louis", "The University of Montana", "University of Nebraska at Omaha", "University of Nevada-Las Vegas", "University of Nevada-Reno", "University of New Hampshire-Main Campus", "Kean University", "Monmouth University", "Montclair State University", "Ramapo College of New Jersey", "Rutgers University-New Brunswick", "Seton Hall University", "Stockton University", "New Mexico State University-Main Campus", "Western New Mexico University", "Adelphi University", "Columbia University in the City of New York", "College of Staten Island CUNY", "CUNY Hunter College", "CUNY Lehman College", "Daemen College", "Fordham University", "Keuka College", "Long Island University", "Nazareth College", "New York University", "Roberts Wesleyan College", "SUNY at Albany", "Binghamton University", "University at Buffalo", "Stony Brook University", "Syracuse University", "Touro College", "Yeshiva University", "Appalachian State University", "East Carolina University", "Fayetteville State University", "North Carolina A & T State University", "University of North Carolina at Chapel Hill", "University of North Carolina at Charlotte", "University of North Carolina at Greensboro", "North Carolina Central University", "North Carolina State University at Raleigh", "University of North Carolina Wilmington", "University of North Carolina at Pembroke", "Western Carolina University", "University of North Dakota", "University of Akron Main Campus", "Case Western Reserve University", "University of Cincinnati-Main Campus", "Cleveland State University", "Miami University-Oxford", "Ohio State University-Main Campus", "Ohio University-Main Campus", "University of Toledo", "Wright State University-Main Campus", "Youngstown State University", "University of Oklahoma-Norman Campus", "George Fox University", "Pacific University", "Portland State University", "California University of Pennsylvania", "Edinboro University of Pennsylvania", "Kutztown University of Pennsylvania", "Marywood University", "Millersville University of Pennsylvania", "University of Pennsylvania", "Shippensburg University of Pennsylvania", "Temple University", "West Chester University of Pennsylvania", "Widener University", "Rhode Island College", "University of South Carolina-Columbia", "Winthrop University", "University of South Dakota", "Austin Peay State University", "East Tennessee State University", "University of Memphis", "Middle Tennessee State University", "Southern Adventist University", "The University of Tennessee-Chattanooga", "The University of Tennessee-Knoxville", "Tennessee State University", "Union University", "Abilene Christian University", "Baylor University", "Texas A & M University-Commerce", "University of Houston", "Our Lady of the Lake University", "The University of Texas Rio Grande Valley", "Stephen F Austin State University", "Texas State University", "Tarleton State University", "The University of Texas at Arlington", "The University of Texas at Austin", "The University of Texas at El Paso", "Texas Christian University", "The University of Texas at San Antonio", "Texas Tech University", "West Texas A & M University", "Brigham Young University-Provo", "Utah State University", "University of Utah", "University of Vermont", "George Mason University", "Norfolk State University", "Radford University", "Virginia Commonwealth University", "Eastern Washington University", "Seattle University", "Walla Walla University", "University of Washington-Seattle Campus", "Concord University", "Marshall University", "West Virginia University", "University of Wisconsin-Green Bay", "University of Wisconsin-Oshkosh", "University of Wisconsin-Madison", "University of Wisconsin-Milwaukee", "University of Wyoming", "Inter American University of Puerto Rico-Arecibo", "University of Puerto Rico-Rio Piedras", "Universidad Ana G. Mendez-Gurabo Campus", "California State University-San Marcos", "California State University-Monterey Bay", "Florida Gulf Coast University"
#> $ control <dbl+lbl> 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 2, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 2, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1
#> $ ccbasic <dbl+lbl> 18, 19, 15, 17, 18, 18, 15, 16, 15, 16, 16, 18, 18, 18, 18, 18, 17, 18, 18, 18, 18, 18, 18, 15, 19, 16, 18, 18, 15, 15, 16, 18, 15, 17, 17, 18, 16, 16, 17, 15, 16, 15, 15, 16, 18, 15, 18, 19, 15, 15, 20, 17, 15, 18, 16, 18, 17, 18, 16, 18, 15, 16, 16, 18, 18, 17, 16, 17, 16, 19, 20, 20, 15, 18, 18, 15, 18, 17, 16, 20, 18, 15, 15, 17, 17, 17, 18, 15, 19, 15, 16, 16, 18, 16, 18, 15, 15, 18, 18, 17, 18, 19, 17, 16, 17, 18, 18, 15, 15, 15, 16, 18, 18, 15, 19, 18, 17, 17, 16, 20, 15, 15, 16, 16, 18, 16, 17, 15, 16, 16, 15, 15, 15, 18, 18, 16, 19, 15, 16, 18, 16, 18, 17, 15, 18, 18, 18, 17, 16, 19, 17, 18, 15, 18, 15, 15, 15, 15, 15, 17, 16, 18, 16, 19, 16, 15, 16, 16, 18, 15, 16, 18, 18, 16, 16, 15, 15, 16, 16, 15, 16, 16, 16, 18, 15, 17, 17, 16, 18, 18, 18, 18, 18, 15, 18, 15, 18, 17, 18, 15, 18, 16, 18, 16, 16, 17, 19, 17, 15, 16, 17, 18, 16, 17, 15, 17, 16, 17, 16, 18, 15, 15, 15, 16, 16, 15, 18, 16, 16, 15, 16, 15, 19, 18, 15, 18, 17, 20, 15, 19, 16, 15, 19, 18, 15, 15, 16, 19, 16, 17, 18, 19, 18
#> $ stabbr <chr> "AL", "AL", "AL", "AL", "AL", "AK", "AZ", "AR", "AR", "AR", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CO", "CO", "CO", "CT", "CT", "CT", "CT", "DE", "DC", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "GA", "GA", "GA", "GA", "GA", "HI", "HI", "ID", "ID", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IN", "IN", "IN", "IN", "IA", "IA", "IA", "KS", "KS", "KS", "KS", "KY", "KY", "KY", "KY", "KY", "KY", "KY", "LA", "LA", "LA", "LA", "ME", "ME", "ME", "MD", "MD", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MN", "MN", "MN", "MN", "MN", "MN", "MN", "MS", "MS", "MS", "MO", "MO", "MO", "MO", "MO", "MO", "MO", "MT", "NE", "NV", "NV", "NH", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NM", "NM", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "ND", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OK", "OR", "OR", "OR", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "RI", "SC", "SC", "SD", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "UT", "UT", "UT", "VT", "VA", "VA", "VA", "VA", "WA", "WA", "WA", "WA", "WV", "WV", "WV", "WI", "WI", "WI", "WI", "WY", "PR", "PR", "PR", "CA", "CA", "FL"
#> $ region <dbl+lbl> 5, 5, 5, 5, 5, 8, 6, 5, 5, 5, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 7, 7, 7, 1, 1, 1, 1, 2, 2, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 8, 8, 7, 7, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 4, 4, 4, 4, 4, 4, 4, 7, 4, 8, 8, 1, 2, 2, 2, 2, 2, 2, 2, 6, 6, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 6, 8, 8, 8, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 5, 5, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 1, 5, 5, 5, 5, 8, 8, 8, 8, 5, 5, 5, 3, 3, 3, 3, 7, 9, 9, 9, 8, 8, 5
#> $ city <chr> "Normal", "Montgomery", "Tuscaloosa", "Birmingham", "Troy", "Anchorage", "Tempe", "Little Rock", "Fayetteville", "Jonesboro", "Azusa", "Bakersfield", "Turlock", "San Bernardino", "Chico", "Carson", "Fresno", "Fullerton", "Hayward", "Long Beach", "Los Angeles", "Northridge", "Sacramento", "Los Angeles", "Arcata", "San Diego", "San Francisco", "San Jose", "Los Angeles", "Fort Collins", "Denver", "Denver", "Storrs", "Hamden", "West Hartford", "New Haven", "Dover", "Washington", "Miami", "Orlando", "Tallahassee", "Miami", "Tallahassee", "Fort Lauderdale", "Saint Leo", "Tampa", "Pensacola", "Albany", "Atlanta", "Athens", "Savannah", "Valdosta", "Honolulu", "Honolulu", "Boise", "Nampa", "Aurora", "Chicago", "Chicago", "University Park", "Chicago", "Normal", "Chicago", "Chicago", "River Forest", "Joliet", "Carbondale", "Edwardsville", "Indianapolis", "South Bend", "Gary", "Richmond", "Iowa City", "Cedar Falls", "Davenport", "Lawrence", "Wichita", "Topeka", "Wichita", "Wilmore", "Campbellsville", "Lexington", "Louisville", "Highland Heights", "Louisville", "Bowling Green", "Grambling", "Baton Rouge", "New Orleans", "New Orleans", "Orono", "Biddeford", "Portland", "Baltimore", "Salisbury", "Chestnut Hill", "Boston", "Bridgewater", "Salem", "Boston", "Springfield", "Westfield", "Berrien Springs", "Ypsilanti", "Big Rapids", "Allendale", "Livonia", "Ann Arbor", "East Lansing", "Detroit", "Kalamazoo", "Minneapolis", "Mankato", "Minneapolis", "Duluth", "Saint Cloud", "Duluth", "Saint Paul", "Jackson", "Itta Bena", "Hattiesburg", "Columbia", "Kansas City", "Saint Louis", "Parkville", "Saint Louis", "Springfield", "Saint Louis", "Missoula", "Omaha", "Las Vegas", "Reno", "Durham", "Union", "West Long Branch", "Montclair", "Mahwah", "New Brunswick", "South Orange", "Galloway", "Las Cruces", "Silver City", "Garden City", "New York", "Staten Island", "New York", "Bronx", "Amherst", "Bronx", "Keuka Park", "Brookville", "Rochester", "New York", "Rochester", "Albany", "Vestal", "Buffalo", "Stony Brook", "Syracuse", "New York", "New York", "Boone", "Greenville", "Fayetteville", "Greensboro", "Chapel Hill", "Charlotte", "Greensboro", "Durham", "Raleigh", "Wilmington", "Pembroke", "Cullowhee", "Grand Forks", "Akron", "Cleveland", "Cincinnati", "Cleveland", "Oxford", "Columbus", "Athens", "Toledo", "Dayton", "Youngstown", "Norman", "Newberg", "Forest Grove", "Portland", "California", "Edinboro", "Kutztown", "Scranton", "Millersville", "Philadelphia", "Shippensburg", "Philadelphia", "West Chester", "Chester", "Providence", "Columbia", "Rock Hill", "Vermillion", "Clarksville", "Johnson City", "Memphis", "Murfreesboro", "Collegedale", "Chattanooga", "Knoxville", "Nashville", "Jackson", "Abilene", "Waco", "Commerce", "Houston", "San Antonio", "Edinburg", "Nacogdoches", "San Marcos", "Stephenville", "Arlington", "Austin", "El Paso", "Fort Worth", "San Antonio", "Lubbock", "Canyon", "Provo", "Logan", "Salt Lake City", "Burlington", "Fairfax", "Norfolk", "Radford", "Richmond", "Cheney", "Seattle", "College Place", "Seattle", "Athens", "Huntington", "Morgantown", "Green Bay", "Oshkosh", "Madison", "Milwaukee", "Laramie", "Arecibo", "San Juan", "Gurabo", "San Marcos", "Seaside", "Fort Myers"
#> $ locale <dbl+lbl> 12, 12, 12, 21, 33, 11, 12, 12, 13, 13, 21, 11, 23, 12, 13, 13, 11, 21, 21, 11, 11, 11, 11, 11, 33, 11, 11, 11, 11, 12, 11, 11, 21, 21, 21, 12, 13, 11, 21, 21, 12, 21, 12, 21, 23, 11, 13, 13, 11, 12, 12, 13, 11, 11, 12, 22, 21, 11, 11, 41, 11, 22, 11, 11, 21, 21, 13, 21, 11, 12, 13, 41, 13, 13, 12, 13, 11, 12, 11, 31, 32, 11, 11, 21, 11, 13, 32, 12, 11, 11, 23, 22, 13, 11, 23, 13, 11, 21, 21, 11, 12, 21, 31, 21, 32, 21, 13, 12, 13, 11, 13, 11, 13, 11, 13, 13, 13, 11, 12, 33, 13, 12, 11, 21, 21, 11, 12, 21, 13, 11, 12, 11, 23, 21, 21, 21, 21, 13, 21, 22, 22, 33, 21, 11, 11, 11, 11, 21, 11, 32, 21, 21, 11, 21, 13, 22, 21, 21, 12, 11, 11, 32, 13, 12, 11, 13, 11, 11, 11, 11, 12, 32, 32, 13, 12, 11, 11, 11, 31, 11, 32, 11, 21, 13, 22, 31, 21, 11, 23, 31, 31, 13, 21, 11, 31, 11, 21, 21, 21, 12, 13, 32, 12, 13, 11, 12, 21, 12, 12, 11, 13, 12, 12, 32, 11, 11, 13, 33, 13, 33, 11, 11, 11, 11, 11, 11, 31, 12, 13, 12, 13, 21, 12, 23, 12, 31, 11, 23, 11, 32, 13, 13, 12, 13, 11, 11, 33, 13, 11, 21, 21, 22, 21
#> $ urban <dbl+lbl> 2, 2, 2, 3, 4, 1, 2, 2, 2, 2, 3, 1, 3, 2, 2, 2, 1, 3, 3, 1, 1, 1, 1, 1, 4, 1, 1, 1, 1, 2, 1, 1, 3, 3, 3, 2, 2, 1, 3, 3, 2, 3, 2, 3, 3, 1, 2, 2, 1, 2, 2, 2, 1, 1, 2, 3, 3, 1, 1, 4, 1, 3, 1, 1, 3, 3, 2, 3, 1, 2, 2, 4, 2, 2, 2, 2, 1, 2, 1, 4, 4, 1, 1, 3, 1, 2, 4, 2, 1, 1, 3, 3, 2, 1, 3, 2, 1, 3, 3, 1, 2, 3, 4, 3, 4, 3, 2, 2, 2, 1, 2, 1, 2, 1, 2, 2, 2, 1, 2, 4, 2, 2, 1, 3, 3, 1, 2, 3, 2, 1, 2, 1, 3, 3, 3, 3, 3, 2, 3, 3, 3, 4, 3, 1, 1, 1, 1, 3, 1, 4, 3, 3, 1, 3, 2, 3, 3, 3, 2, 1, 1, 4, 2, 2, 1, 2, 1, 1, 1, 1, 2, 4, 4, 2, 2, 1, 1, 1, 4, 1, 4, 1, 3, 2, 3, 4, 3, 1, 3, 4, 4, 2, 3, 1, 4, 1, 3, 3, 3, 2, 2, 4, 2, 2, 1, 2, 3, 2, 2, 1, 2, 2, 2, 4, 1, 1, 2, 4, 2, 4, 1, 1, 1, 1, 1, 1, 4, 2, 2, 2, 2, 3, 2, 3, 2, 4, 1, 3, 1, 4, 2, 2, 2, 2, 1, 1, 4, 2, 1, 3, 3, 3, 3
#> $ cipdig2 <chr> "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44", "44"
#> $ cipcode <chr> "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407", "4407"
#> $ cipdesc <chr> "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work.", "Social Work."
#> $ credlev <dbl+lbl> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5
#> $ creddesc <chr> "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree"
#> $ ipedscount1 <dbl> 92, 7, 189, 8, 106, 20, NA, 66, 17, 38, 78, 67, 66, 105, 40, 74, 65, 103, 90, 222, 143, 178, 109, 101, 62, 131, 31, 88, 1472, 57, 278, 101, 160, 31, 44, 82, 19, 12, 178, 131, 16, 19, NA, 31, 95, 127, 0, 26, 62, 152, 39, 38, 102, 32, 112, 54, 379, 28, 19, 53, 202, 29, 299, 0, 115, 34, 73, 31, 350, NA, NA, 13, 97, 37, 35, 180, 86, 55, 54, 14, 71, 96, 206, 62, 24, 63, 30, 97, 130, 77, 37, 328, 29, 69, 126, 248, 204, 60, 97, 330, 151, 64, 28, 66, 29, 177, 21, 336, 39, 343, 141, 76, 29, 131, 31, 34, 33, 140, 90, NA, 63, 91, 62, 54, 23, 83, 35, 197, 25, 84, 75, 45, 72, 42, 119, 59, 37, 660, 18, 60, 68, 98, 268, 454, 27, 465, 91, 22, 622, 18, 14, 39, 567, 49, 166, 66, 217, 214, 102, 90, 118, 47, 69, 65, 27, 128, 73, 27, 81, 72, 41, 60, 33, 78, 70, 168, 66, 108, 18, 242, 36, 35, 37, 46, 153, 44, 12, 205, 58, 153, 25, 131, 65, 197, 36, 189, 80, 95, 84, 274, 54, 40, 32, 49, 56, 25, 33, NA, 220, 17, 50, 15, 67, 72, 167, 303, 54, 51, 111, 0, 458, 146, 34, 27, 55, 14, 19, 41, 2, 171, 29, 54, 62, 34, 170, 125, 0, 85, 203, 43, NA, 67, 53, 8, 176, 154, 22, 31, 73, 37, 58, 36, 17
#> $ ipedscount2 <dbl> 79, 25, 225, 13, 86, 19, NA, 69, 51, 43, 69, 74, 101, 109, 81, 70, 50, 101, 139, 219, 139, 182, 120, 108, 52, 101, 29, 159, 1383, 83, 279, 123, 142, 22, 60, 81, 34, 26, 130, 143, 19, 0, NA, 47, 86, 90, 0, 17, 60, 170, 34, 60, 95, 20, 187, 48, 325, 38, 17, 54, 239, 24, 277, 29, 101, 21, 60, 29, 323, NA, NA, 0, 67, 38, 33, 204, 41, 59, 56, 19, 91, 90, 197, 56, 24, 58, 15, 128, 87, 74, 36, 339, 30, 71, 160, 265, 229, 55, 129, 545, 111, 65, 19, 75, 37, 145, 48, 329, 21, 335, 131, 55, 27, 137, 24, 44, 39, 115, 76, NA, 88, 75, 69, 52, 41, 93, 30, 215, 36, 80, 75, 80, 94, 60, 90, 68, 56, 716, 37, 52, 50, 142, 263, 509, 29, 559, 87, 12, 659, 25, 108, 42, 567, 46, 159, 72, 214, 238, 70, 132, 86, 33, 66, 64, 19, 127, 79, 21, 82, 77, 41, 39, 40, 73, 69, 259, 86, 64, 23, 266, 42, 41, 32, 44, 154, 35, 22, 245, 30, 202, 39, 104, 60, 195, 27, 154, 102, 152, 79, 237, 60, 0, 22, 47, 52, 28, 24, 16, 231, 22, 88, 16, 80, 66, 161, 334, 72, 48, 124, 18, 515, 135, 37, 22, 84, 11, 27, 40, 98, 164, 28, 83, 80, 40, 199, 88, 26, 77, 244, 58, 60, 71, 44, 8, 158, 141, 20, 3, 47, 21, 57, 49, 19
#> $ debt_all_stgp_eval_n <dbl> 146, NA, 244, 17, 145, 20, 502, 104, 47, 27, 130, 42, 105, 170, 75, 99, 43, 124, 147, 285, 188, 217, 139, 151, 78, 122, 31, 47, 2410, 82, 352, 160, 202, 36, 55, 122, 48, 17, 247, 127, 26, NA, NA, 54, 152, 162, NA, NA, 93, 204, 61, 34, 128, 21, 246, 92, 585, 57, 32, 77, 312, 34, 366, 23, 148, 32, 111, 43, 351, NA, NA, NA, 118, 54, 61, 306, 92, 86, 86, 29, 134, 135, 291, 98, 39, 87, 38, 76, 172, 66, 62, 562, 40, 120, 191, 358, 385, 75, 163, 750, 201, 102, 29, 120, 62, 231, 50, 484, 43, 516, 199, 117, 41, 140, 22, 52, 52, 180, 137, NA, 54, 100, 95, 68, 50, 137, 44, 249, 44, 110, 107, 83, 132, 80, 157, 67, 33, 1059, 50, 89, 70, 57, 362, 648, 37, 646, 144, NA, 985, NA, 151, NA, 675, 80, 252, 104, 320, 368, 133, 185, 107, 57, 79, 52, 25, 169, 102, 39, 149, 110, 45, 77, 57, 106, 102, 337, 109, 143, 32, 379, 65, 62, 53, 72, 226, 67, 29, 349, 65, 292, 36, 177, 94, 242, 48, 287, 61, 201, 120, 358, 87, NA, 30, 73, 89, 44, 43, NA, 234, 34, 121, 15, 90, 104, 236, 562, 110, 81, 162, NA, 705, 171, 44, 27, 102, NA, 15, 40, 58, 254, 36, 82, 130, 58, 254, 166, 22, 136, 381, 74, NA, 95, 65, 10, 132, 145, 18, 23, 53, 44, 87, 58, 19
#> $ debt_all_stgp_eval_mean <dbl> 51788, 38001, 32830, 49278, 30072, 30364, 45258, 41114, 27713, 30749, 52599, 35504, 29260, 34215, 23963, 30955, 25310, 30502, 41701, 29514, 31228, 40156, 28069, 51668, 35344, 29289, 30555, 31873, 113762, 42076, 68054, 33513, 35729, 66125, 48283, 34297, 36188, 52931, 53125, 38754, 51889, 51313, 45013, 73360, 52571, 36879, 20730, 57667, 39799, 43011, 39736, 54598, 32837, 45826, 30178, 39716, 34247, 62017, 76163, 37720, 41770, 35315, 66401, 24445, 46415, 32551, 34114, 23673, 40289, 36999, 46987, 43838, 47358, 27987, 61776, 37566, 49449, 38559, 33746, 44773, 24545, 41439, 43899, 36260, 32562, 31538, 48845, 38704, 45271, 74833, 43484, 51835, 38680, 39345, 33723, 52959, 53233, 41195, 35397, 74968, 59338, 27629, 60619, 51418, 33175, 44150, 23785, 47297, 52884, 39517, 48476, 40906, 25346, 44435, 45190, 25411, 46643, 51357, 52132, 44738, 41514, 29131, 42930, 34593, 27922, 54328, 37145, 58537, 43902, 34127, 46631, 22823, 50711, 48132, 43835, 31239, 31038, 48412, 60068, 28584, 30185, 40880, 62589, 80957, 29854, 38164, 33472, 33170, 54277, 34934, 76214, 44523, 85772, 38879, 35609, 40935, 38913, 37367, 72816, 60442, 45677, 22968, 38103, 32348, 39727, 55365, 28665, 23703, 44724, 31732, 33050, 33942, 33058, 34532, 36348, 86730, 39054, 44679, 29028, 39874, 24376, 30908, 38900, 43045, 39489, 37261, 61686, 47388, 39681, 43393, 33888, 50849, 35271, 70869, 39569, 54001, 42719, 66833, 33500, 48544, 39780, 28435, 26619, 41749, 41437, 27617, 45462, 24228, 44304, 31382, 42968, 44044, 40243, 25793, 38107, 45506, 19140, 24017, 28853, 21751, 35646, 42070, 29456, 39802, 44463, 25378, 28327, 18361, 29569, 34387, 50788, 42113, 49831, 37717, 47034, 40277, 45996, 45953, 51473, 27310, 30568, 43234, 28902, 20741, 36246, 36433, 31190, 22688, 18903, 33732, 54252, 24378, 26507
#> $ debt_all_stgp_eval_mdn <dbl> 50446, 41000, 30750, NA, 23141, 26831, 41001, 43135, 27000, 27050, 52018, 38454, 31428, 35750, 19584, 28500, 25321, 30504, 39682, 28500, 29169, 38842, 27972, 53500, 34812, 26314, 30750, 36726, 118698, 38435, 68635, 33500, 31642, 65677, 45953, 30750, 38000, NA, 44334, 35199, 47880, NA, 41000, 58888, 51250, 30981, NA, 59863, 35600, 41000, 41000, 60613, 29330, 40500, 25601, 41000, 30500, 62761, 79726, 34935, 37045, 36126, 61190, 24000, 41000, 28063, 28500, 18680, 41000, 36989, 43977, NA, 45775, 27200, 55861, 36510, 48026, 34313, 31155, 41000, 20568, 41000, 37173, 30809, 30750, 27643, 48482, 41000, 41000, 77000, 41000, 50227, 39362, 41000, 29722, 50452, 52000, 41000, 32897, 80278, 61500, 28456, 53872, 46154, 30136, 42247, 20500, 41000, 47052, 39456, 42192, 40166, 24000, 41000, 44462, 25000, 46397, 48891, 48307, 52590, 41000, 26842, 37703, 33875, 23541, 50380, 30139, 58260, 46801, 30574, 41000, 20500, 51250, 45000, 41000, 30938, 23500, 41000, 55250, 20500, 28807, 41000, 63934, 76863, 29305, 41000, 32900, 23553, 49000, 40560, 73547, 43000, 82970, 41000, 36000, 41000, 40410, 35476, 70385, 61000, 41000, 19429, 37575, 33368, 38319, 50490, 27471, 25693, 41000, 30750, 30500, 31487, 34144, 29143, 34400, 86000, 37610, 41000, 28112, 39362, 20500, 25000, 30208, 43199, 36034, 35866, 66948, 46666, 38685, 41000, 32740, 50122, 38734, 68834, 39550, 51000, 41000, 67783, 33088, 44900, 41000, 26658, 22627, 37817, 37681, 21940, 41000, NA, 41000, 20500, 41000, NA, 41000, 20549, 37863, 40547, 17500, 22835, 27660, NA, 33801, 39376, 28050, 38738, 39406, 20683, NA, 15810, 32099, 32126, 42539, 40977, 49517, 39071, 41000, 40975, 41000, 44772, 50244, 25000, 26705, 41000, 26049, NA, 36451, 34200, NA, 25500, 16000, 37016, 55604, 19565, 20500
#> $ debt_all_stgp_eval_mdn10yrpay <dbl> 518, 421, 316, NA, 238, 275, 421, 443, 277, 278, 534, 395, 323, 367, 201, 293, 260, 313, 407, 293, 299, 399, 287, 549, 357, 270, 316, 377, 1219, 395, 705, 344, 325, 674, 472, 316, 390, NA, 455, 361, 492, NA, 421, 605, 526, 318, NA, 615, 366, 421, 421, 622, 301, 416, 263, 421, 313, 644, 819, 359, 380, 371, 628, 246, 421, 288, 293, 192, 421, 380, 452, NA, 470, 279, 574, 375, 493, 352, 320, 421, 211, 421, 382, 316, 316, 284, 498, 421, 421, 791, 421, 516, 404, 421, 305, 518, 534, 421, 338, 824, 631, 292, 553, 474, 309, 434, 210, 421, 483, 405, 433, 412, 246, 421, 457, 257, 476, 502, 496, 540, 421, 276, 387, 348, 242, 517, 309, 598, 481, 314, 421, 210, 526, 462, 421, 318, 241, 421, 567, 210, 296, 421, 656, 789, 301, 421, 338, 242, 503, 416, 755, 442, 852, 421, 370, 421, 415, 364, 723, 626, 421, 199, 386, 343, 393, 518, 282, 264, 421, 316, 313, 323, 351, 299, 353, 883, 386, 421, 289, 404, 210, 257, 310, 444, 370, 368, 687, 479, 397, 421, 336, 515, 398, 707, 406, 524, 421, 696, 340, 461, 421, 274, 232, 388, 387, 225, 421, NA, 421, 210, 421, NA, 421, 211, 389, 416, 180, 234, 284, NA, 347, 404, 288, 398, 405, 212, NA, 162, 330, 330, 437, 421, 508, 401, 421, 421, 421, 460, 516, 257, 274, 421, 267, NA, 374, 351, NA, 262, 164, 380, 571, 201, 210
#> $ earn_count_wne_hi_1yr <dbl> 138, NA, 276, NA, 104, 24, 513, 110, 31, 39, 132, 113, 96, 163, 70, 120, 99, 161, 156, 385, 197, 271, 197, 162, 86, 173, 47, 136, 2360, 74, 408, 161, 239, 44, 25, 117, 31, 21, 261, 186, 20, 64, 379, 32, 129, 154, 50, 37, 91, 248, 62, 39, 151, 37, 179, 81, 543, 53, 30, 79, 339, 44, 460, NA, 158, 37, 111, 47, 362, 49, 49, 12, 140, 63, 51, 293, 99, 72, 84, 34, 96, 139, 312, 107, 33, 94, 52, 52, 146, 74, 66, 528, 55, 120, 189, 389, 398, 87, 149, 446, 242, 114, 22, 107, 45, 251, 18, 494, 60, 528, 249, 115, 24, 80, 17, 52, 53, 216, 130, 30, 100, 116, 98, 81, 16, 130, 52, 239, 48, 114, 120, 62, 124, 74, 209, 73, 34, 1003, 15, 102, 102, NA, 366, 578, 43, 666, 143, 25, 927, 24, 168, 31, 762, 81, 279, 104, 301, 312, 148, 152, 113, 72, 118, 51, 54, 183, 116, 25, 127, 117, 44, 104, 63, 125, 115, 252, 114, 163, 30, 344, 68, 62, 51, 64, 212, 53, 26, 362, 75, 214, 48, 191, 116, 273, 53, 340, 115, 163, 129, 410, 88, 74, 43, 76, 74, 47, 37, NA, 287, 31, 106, NA, 98, 122, 228, 399, 96, 99, 168, NA, 665, 215, 62, 29, 99, NA, NA, 58, 21, 275, 52, 119, 94, 59, 250, 164, NA, 138, 448, 54, 18, 108, 65, 34, 159, 108, 26, 22, 35, 35, 72, 55, 25
#> $ earn_mdn_hi_1yr <dbl> 38065, NA, 39254, NA, 39609, 50606, 46843, 47377, 44276, 44170, 54091, 57770, 58522, 54732, 49611, 60165, 62829, 54696, 69114, 59506, 56979, 54348, 56693, 59124, 53080, 50717, 68592, 72850, 51438, 43504, 44912, 43888, 49064, 46738, 48641, 50161, 46087, 42682, 42584, 41524, 39009, 45919, 42821, 41342, 42384, 41193, 38721, 43696, 41751, 42390, 39214, 42012, 47944, 43984, 42961, 45752, 43252, 45435, 44356, 44845, 45348, 41193, 44381, NA, 43114, 39153, 38122, 42309, 44122, 39909, 45435, 42682, 44001, 43426, 42682, 44212, 43128, 43984, 40161, 35416, 36398, 38674, 40082, 42806, 40017, 38083, 37808, 38443, 39326, 42433, 44852, 45963, 42682, 49072, 47357, 49179, 50115, 53219, 50567, 49100, 50105, 51880, 40095, 46899, 45584, 43553, 39369, 45797, 43575, 43178, 44209, 49498, 49520, 49503, 50856, 48823, 45554, 50009, 33815, 32391, 37856, 41971, 45052, 42123, 39369, 40614, 44595, 43832, 39369, 44209, 48883, 51690, 46300, 42682, 46714, 52607, 44468, 48104, 42123, 47136, 45190, NA, 49397, 53202, 54331, 54467, 54073, 41725, 50836, 46924, 48579, 48041, 51487, 44595, 47992, 45500, 42742, 47869, 45305, 50395, 49962, 41069, 43749, 40408, 43087, 43798, 42174, 42433, 42841, 43264, 42495, 41420, 41844, 51346, 41441, 45284, 41565, 41823, 41342, 43496, 43319, 43290, 44666, 42479, 46182, 43351, 48432, 50186, 41651, 44087, 43426, 44431, 41342, 46999, 47046, 46902, 49939, 46336, 50194, 39556, 40621, 44468, 38289, 38649, 43240, 42682, 41342, NA, 42196, 38829, 38787, NA, 43000, 49797, 46053, 45991, 50272, 38597, 45365, NA, 46449, 45949, 44356, 47260, 46889, NA, NA, 44711, 45852, 47409, 45340, 51762, 45604, 40089, 44699, 51118, NA, 43798, 51946, 39297, 38289, 43000, 44861, 49660, 45785, 47494, 46478, 20140, 23538, 22810, 48752, 62463, 50105
#> $ earn_count_wne_hi_2yr <dbl> 83, NA, 292, NA, 20, 27, 503, 107, 36, 33, 109, 88, 94, 136, 97, 111, 92, 152, 142, 350, 154, 255, 193, 160, 73, 76, 45, 81, 2263, 86, 393, 140, 269, 30, 26, 97, 51, 22, 317, 86, 15, 90, 296, 25, 57, 98, 70, 27, 69, 224, 62, 45, 128, 19, 183, 37, 414, 57, 35, 95, 339, 29, 259, NA, 108, 21, 101, 23, 299, 39, 47, NA, 125, 55, 47, 143, 74, 63, 96, 46, 58, 158, 289, 111, 15, 86, 60, 17, 126, 72, 58, 372, 49, 117, 139, 362, 425, 77, 117, 270, 121, 103, 13, 92, 19, 214, NA, 375, 48, 510, 202, 94, 17, 19, NA, 48, 55, 195, 107, 46, 43, 112, 95, 71, NA, 107, 42, 115, 43, 86, 118, 44, 85, 74, 221, 40, NA, 478, NA, 81, 89, NA, 301, 595, 30, 582, 142, NA, 811, NA, 199, 13, 712, 37, 137, 96, 136, 267, 70, 79, 82, 55, 97, 74, 29, 92, 97, NA, 80, 60, 30, 90, 62, 89, 106, 205, 68, 154, 32, 348, 71, 70, 39, 38, 182, 19, 14, 353, 69, 88, 58, 140, 102, 267, 42, 324, 102, 171, 104, 433, 78, 39, 25, 67, 53, 26, 17, NA, 291, 30, 107, 15, 93, 88, 208, 212, 80, 83, 158, NA, 483, 236, 53, 25, 115, NA, NA, 53, 18, 135, 43, 124, 45, 56, 234, 140, NA, 119, 453, 31, NA, 128, 24, 21, 250, 91, 29, NA, 37, 18, 43, 44, 26
#> $ earn_mdn_hi_2yr <dbl> 37819, NA, 38981, NA, 38289, 51750, 46118, 47877, 44595, 45383, 54082, 58943, 57796, 58503, 54073, 60096, 56641, 55534, 64087, 59443, 60585, 58035, 56114, 59742, 53045, 49990, 70680, 72320, 52078, 44133, 44882, 46422, 49929, 48432, 44021, 50263, 47260, 44737, 43950, 35861, 35416, 46087, 43054, 33993, 42682, 42542, 38433, 43128, 40017, 42138, 40697, 41193, 47729, 42682, 44399, 40768, 43528, 39639, 47260, 41479, 43182, 44895, 43426, NA, 43054, 42682, 39045, 38721, 44093, 43319, 44755, NA, 47361, 44508, 43426, 43605, 41937, 42868, 38516, 39153, 37208, 38736, 42123, 42276, 39369, 38505, 36745, 36455, 38195, 41689, 43798, 44399, 42203, 47673, 45500, 50000, 50336, 54053, 50606, 49378, 51794, 47260, 33993, 47871, 43240, 43269, NA, 46342, 46478, 44269, 44323, 54768, 49019, 54435, NA, 47520, 47553, 50806, 35314, 33007, 37748, 41362, 42961, 45647, NA, 40589, 42185, 43333, 38443, 44765, 52464, 52334, 46478, 42276, 45554, 47260, NA, 46886, NA, 47092, 42263, NA, 49714, 53587, 52941, 52377, 53550, NA, 50971, NA, 45472, 46321, 50280, 40017, 44698, 45061, 40546, 48980, 45408, 48162, 47260, 42510, 42363, 42961, 44021, 43575, 42487, NA, 42522, 39119, 45584, 41087, 44170, 50856, 43016, 44800, 41631, 43626, 39249, 43371, 44227, 44930, 46673, 38048, 45008, 46924, 42123, 49962, 40125, 46272, 43493, 44335, 42821, 47846, 46924, 47334, 46148, 48010, 48864, 39353, 42123, 42073, 39153, 37907, 47650, 39729, 38829, NA, 41007, 41937, 39693, 43426, 40269, 45030, 48971, 46177, 50258, 42682, 44426, NA, 46168, 45600, 48112, 46087, 48628, NA, NA, 46193, 47260, 45870, 44635, 48600, 45500, 41007, 44987, 48501, NA, 42682, 49646, 40827, NA, 42402, 44933, 50105, 46332, 48225, 49631, NA, 25194, 19227, 49270, 55964, 46869
#> $ tuit_grad_res <dbl> 8130, 6174, 10470, 18530, 7146, 9768, 10810, 7680, 7379, 4626, 16224, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 11220, 6738, 6738, 6738, 6738, 41592, 9628, 45288, 7568, 13726, 17730, 12822, 6497, 5160, 17100, 17820, 6916, 8019, 8912, 9684, 18373, 9630, 8350, 7088, 3402, 6876, 8492, 3528, 4374, 15288, 17190, 6232, 8851, 10800, 5580, 18960, 7368, 13263, 7466, 18594, 6408, 17993, 13302, 10524, 6312, 8331, 6648, 6648, 6648, 8856, 8592, 16020, 9480, 9306, 8250, 5173, 10242, 11904, 10925, 12246, 10008, 13608, 11400, 5110, 9132, 6024, 49030, 7524, 19936, 6840, 7074, 6858, 27216, 49176, 1675, 2520, 20556, 29640, 5724, 25128, 15120, 7046, 15408, 13410, 21466, 16764, 14746, 13312, 12778, 6849, 16240, 16240, 7373, 11160, 24386, 7141, 6858, 7549, 8462, 6462, 10668, 8025, 19350, 4644, 48950, 4135, 4649, 4968, 4752, 13840, 13156, 24156, 10464, 14545, 16536, 21078, 10686, 4088, 3026, 37623, 43552, 10130, 10130, 10130, 23208, 32160, 27087, 28272, 21120, 39936, 13482, 10870, 10870, 10870, 10870, 34632, 16200, 19800, 4744, 4656, 3371, 4545, 9643, 4252, 5117, 4647, 8088, 4448, 3639, 4348, 7185, 7731, 42576, 12790, 9565, 12890, 11560, 9510, 13166, 13474, 8492, 4886, 15504, 30421, 13248, 11592, 8694, 8694, 9300, 11592, 32286, 11592, 15786, 11592, 24800, 6696, 12398, 14312, 7516, 8300, 7992, 8820, 7974, 11070, 8100, 11044, 8380, 6870, 19890, 28494, 3630, 7956, 15390, 5439, 4896, 6167, 3672, 7141, 11300, 4497, 26640, 5186, 5400, 4402, 6680, 5323, 6473, 15096, 10628, 7148, 7868, 10976, 10953, 19353, 23088, 15207, 7600, 6298, 9000, 7640, 7640, 10728, 10387, 4338, 3780, 2380, 2652, 6738, 6738, 6974
#> $ fee_grad_res <dbl> 1236, 2284, 0, 610, 802, 1424, 696, 1604, 971, 1292, 220, 1385, 1256, 1138, 1568, 951, 841, 1088, 1092, 988, 911, 1115, 1428, 1463, 1737, 1612, 1012, 1946, 713, 2088, 303, 1073, 2270, 720, 828, 4722, 350, 526, 0, 1956, 1857, 2185, 1859, 802, 0, 2078, 1974, 1602, 2128, 2270, 1758, 2116, 880, 130, 2208, 120, 0, 3196, 330, 1900, 3080, 1504, 848, 1389, 327, 375, 4059, 1642, 1064, 595, 595, 595, 1501, 1211, 280, 958, 406, 110, 905, 0, 300, 1311, 196, 384, 0, 0, 2012, 2755, 1934, 1980, 1142, 686, 830, 1404, 1512, 90, 710, 8563, 4671, 162, 195, 0, 690, 1235, 0, 0, 0, 328, 0, 1757, 923, 0, 714, 1495, 1243, 883, 0, 214, 120, 20, 110, 1114, 1009, 0, 0, 546, 910, 330, 1758, 1441, 532, 535, 2080, 3316, 700, 1676, 3131, 2097, 644, 3214, 853, 1624, 1335, 2002, 560, 308, 430, 100, 491, 111, 1904, 210, 2432, 300, 1824, 2051, 2477, 1696, 1242, 1000, 225, 2977, 2632, 2162, 2902, 1963, 3026, 2636, 2477, 2484, 2595, 2285, 2844, 1458, 1405, 34, 1678, 114, 638, 865, 0, 1555, 0, 410, 3283, 0, 213, 1317, 3916, 2490, 1795, 1415, 3306, 3318, 3384, 890, 2399, 300, 482, 400, 300, 1042, 1473, 1379, 1643, 1260, 0, 1776, 1790, 1040, 20, 0, 3006, 2146, 982, 816, 1169, 1531, 1801, 2437, 1678, 0, 1126, 48, 1915, 2125, 1947, 0, 954, 1054, 1916, 3096, 3420, 3090, 2167, 841, 765, 150, 1059, 150, 1122, 0, 1580, 1122, 1215, 1402, 1335, 714, 144, 900, 1911, 907, 1987
#> $ tuit_grad_nres <dbl> 16260, 12348, 26950, 18530, 14292, 19954, 23480, 17400, 18842, 9252, 16224, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 26322, 15666, 15666, 15666, 15666, 41592, 23604, 45288, 11873, 34762, 17730, 12822, 18102, 11376, 17100, 17820, 25759, 22108, 21393, 24116, 18373, 9630, 19048, 22166, 13590, 22374, 24090, 13068, 15750, 36768, 17190, 20682, 8851, 10800, 10782, 18960, 14736, 22217, 15038, 18594, 12816, 17993, 13302, 26310, 11156, 22985, 15661, 15661, 15661, 26460, 19066, 16020, 22176, 9306, 16786, 12704, 10242, 11904, 27069, 25486, 15390, 13608, 16320, 5110, 9132, 12965, 49030, 24498, 19936, 18468, 13860, 12060, 27216, 49176, 1675, 4140, 20556, 29640, 5724, 25128, 27840, 10569, 15408, 13410, 43346, 32940, 31939, 28195, 12778, 6849, 25120, 25120, 11201, 11160, 24386, 7141, 6858, 16419, 23172, 16685, 26184, 8025, 19350, 9324, 48950, 18742, 12987, 18878, 18662, 27130, 17831, 24156, 15837, 14545, 28128, 21078, 16449, 14254, 8730, 37623, 43552, 18720, 18720, 18720, 23208, 32160, 27087, 28272, 21120, 39936, 13482, 22210, 22210, 22210, 22210, 34632, 16200, 19800, 17913, 17547, 14219, 16950, 26854, 17423, 18566, 17347, 22610, 16667, 13896, 14755, 19184, 13237, 42576, 24532, 16297, 29604, 32008, 17502, 23502, 22890, 12992, 18989, 15504, 30421, 20736, 17400, 13050, 13050, 9300, 17400, 32286, 17400, 21636, 17400, 24800, 13032, 27008, 27570, 14449, 22280, 22248, 17604, 22086, 11070, 24218, 29232, 20020, 6870, 19890, 28494, 10974, 17100, 15390, 12783, 12240, 14327, 11015, 15638, 21518, 12326, 26640, 20785, 12744, 5081, 6680, 18632, 22848, 38160, 29306, 17784, 16394, 22479, 25438, 19353, 23088, 27255, 13252, 16788, 23238, 16771, 16771, 24054, 23424, 12978, 3780, 6498, 2652, 15666, 15666, 28170
#> $ fee_grad_nres <dbl> 1236, 2284, 0, 610, 802, 1758, 696, 1604, 971, 1292, 220, 1385, 1256, 1138, 1568, 951, 841, 1088, 1092, 988, 911, 1115, 1428, 1463, 1737, 1612, 1012, 1946, 713, 2088, 303, 1073, 2270, 720, 828, 5917, 350, 526, 0, 2898, 2561, 2809, 2581, 802, 0, 2078, 2728, 1602, 2128, 2270, 1758, 2116, 880, 130, 2208, 120, 0, 3196, 330, 1900, 3080, 1504, 848, 1389, 327, 375, 4059, 1782, 1064, 595, 595, 595, 1501, 1211, 280, 958, 406, 110, 905, 0, 300, 1311, 196, 384, 0, 0, 11035, 19690, 1934, 1980, 1142, 686, 830, 1404, 1512, 90, 710, 8563, 4671, 162, 195, 0, 690, 1235, 0, 0, 0, 328, 0, 1757, 923, 0, 714, 1495, 1243, 883, 0, 214, 10473, 20, 110, 1114, 1009, 0, 0, 546, 910, 330, 1812, 1441, 532, 535, 2080, 3316, 700, 1676, 3131, 2097, 644, 3214, 853, 1624, 1335, 2002, 560, 308, 430, 100, 491, 111, 1904, 210, 2432, 300, 1824, 2051, 2477, 1696, 1242, 1000, 225, 2977, 2632, 2162, 2902, 1963, 3026, 2636, 2477, 2484, 2595, 2285, 2844, 1458, 1405, 34, 1678, 114, 638, 865, 0, 1555, 0, 410, 3283, 0, 213, 1317, 5119, 3392, 2447, 1415, 3594, 3318, 3672, 890, 2615, 300, 482, 400, 300, 1042, 1473, 1379, 1643, 1260, 0, 1776, 2020, 1040, 20, 0, 3006, 2146, 982, 816, 1169, 1531, 1801, 2437, 1678, 0, 1126, 48, 1915, 2125, 1947, 0, 954, 1054, 1916, 3096, 3420, 3536, 2792, 841, 765, 150, 1059, 150, 1122, 0, 1580, 1122, 1215, 1402, 1335, 714, 144, 900, 1911, 907, 3046
#> $ books_supplies <dbl> 1600, 1600, 1200, 1000, 1129, 1608, 1103, 1715, 1046, 1137, 1792, 1898, 1500, 1791, 1792, 1764, 1792, 1898, 1500, 1898, 1898, 1600, 1792, 1636, 1660, 1818, 1900, 1899, 1200, 1200, 1200, 1200, 850, 800, 1000, 1400, 1700, 1600, 1500, 1152, 1138, 1590, 1000, 1500, 1720, 1200, 1200, 1298, 1600, 1006, 1600, 1200, 952, 1200, 1200, 1200, 1000, 1800, 1104, 900, 1400, 942, 1200, 2400, 1200, 800, 1100, 840, 1204, 1204, 1204, 1204, 950, 900, 1200, 1080, 986, 1000, 1000, 1240, 1100, 1000, 1200, 800, 1260, 1000, 1749, 1160, 1220, 1200, 1000, 1400, 1200, 2500, 1300, 1250, 1000, 800, 1200, 1280, 1000, 1006, 1100, 1000, 914, 700, 1272, 1048, 1076, 1196, 948, 1200, 900, 1000, 1200, 1200, 1150, 1000, 2300, 1400, 1200, 1344, 980, 1000, 1800, 1200, 1100, 980, 1400, 1080, 1298, 1300, 1200, 1384, 1234, 1300, 1569, 1350, 1000, 1597, 1298, 1466, 1020, 1400, 1364, 1364, 1364, 1000, 1012, 1300, 2000, 1100, 1070, 1100, 1200, 1000, 1196, 900, 1440, 778, 1224, 700, 1280, 400, 1400, 1442, 1200, 956, 1500, 1082, 1104, 1505, 2151, 1000, 1000, 1200, 1500, 800, 1216, 1234, 1030, 1150, 1248, 1100, 714, 950, 1050, 2090, 1000, 1000, 1628, 1000, 1000, 1280, 1200, 1000, 1200, 1300, 1200, 1023, 1000, 1200, 1550, 1090, 1415, 1540, 1100, 1400, 1598, 2300, 1250, 1250, 1444, 1400, 1300, 1200, 1210, 1192, 820, 1200, 1206, 662, 1216, 1050, 1000, 1200, 1000, 812, 810, 1232, 1200, 1200, 2535, 1200, 2804, 900, 1500, 825, 825, 1100, 1100, 900, 800, 1000, 1200, 800, 1200, 845, 2168, 1700, 1764, 1339, 1200
#> $ roomboard_off <dbl> 8830, 7320, 13050, 9850, 5815, 11728, 9216, 9406, 10332, 8910, 12494, 13780, 10900, 13770, 11360, 12888, 12492, 13882, 13884, 12910, 13882, 11358, 12492, 10667, 12638, 12050, 13882, 13882, 14348, 9693, 12021, 9694, 12436, 13850, 10750, 9698, 12303, 13040, 11400, 9764, 9636, 11837, 10304, 19125, 11680, 9700, 9354, 10622, 9828, 8032, 7526, 9258, 13030, 17362, 8974, 8350, 3858, 8724, 13387, 10868, 10882, 8082, 11500, 6588, 16699, 7200, 10186, 9211, 9430, 7170, 7170, 7170, 8588, 8629, 9470, 9610, 11169, 10252, 10575, 5210, 3600, 12184, 7538, 9514, 10920, 7713, 10321, 15772, 8780, 13844, 10164, 9700, 9980, 11876, 11352, 10200, 14870, 12200, 10310, 14500, 11890, 10396, 10464, 7400, 8128, 5560, 9550, 10872, 9784, 9134, 9561, 17358, 7112, 9377, 7460, 8230, 8862, 8700, 6100, 7394, 10000, 10298, 9516, 9516, 6400, 10640, 8288, 15596, 8826, 8648, 9190, 10558, 10938, 10973, 8967, 10964, 10849, 17934, 13108, 11942, 8944, 8224, 9720, 17010, 13713, 13713, 13713, 2900, 11924, 10230, 25000, 13150, 17578, 7222, 9750, 8090, 11241, 12900, 15217, 12865, 13283, 8380, 9241, 8070, 7153, 12218, 9823, 8744, 9636, 10635, 8624, 8208, 10100, 7856, 12342, 14298, 12102, 12000, 12454, 11706, 12268, 7514, 11376, 8990, 10280, 10528, 11822, 12200, 10524, 11219, 9438, 10000, 13349, 14536, 9504, 12336, 12860, 8190, 12400, 10540, 7464, 8008, 9711, 7952, 9153, 8246, 8200, 9100, 10238, 6610, 9400, 9310, 10576, 7780, 11067, 7872, 7670, 8868, 7260, 9710, 8410, 10070, 9496, 12000, 9558, 9081, 8582, 7448, 7880, 9936, 10000, 12186, 9490, 8405, 11280, 10941, 11499, 7350, 14625, 8350, 9254, 8340, 7186, 7600, 10446, 10030, 10320, 7314, 11161, 8000, 12826, 15450, 9672
#> $ oth_expense_off <dbl> 3090, 4228, 4116, 5498, 5227, 7568, 4708, 5213, 4104, 5202, 4158, 2924, 2516, 2658, 2478, 2870, 2658, 2924, 2706, 2934, 2924, 2182, 2658, 5140, 2444, 3296, 2966, 2925, 1880, 1360, 2634, 6164, 2650, 2500, 2644, 3972, 5664, 5500, 7700, 4970, 6313, 5354, 4764, 8010, 2552, 4100, 2100, 3860, 4400, 3952, 2326, 4994, 2899, 2220, 4030, 3440, 3520, 4115, 2364, 7000, 3628, 5538, 1600, 6489, 1450, 4120, 2941, 2768, 3798, 3798, 3798, 3798, 3420, 2950, 5924, 3070, 3190, 3581, 4769, 3260, 6150, 3260, 6478, 5364, 3564, 3307, 6871, 5420, 3919, 1060, 2200, 3650, 3000, 4045, 2700, 1700, 1950, 2800, 3402, 2550, 2000, 2434, 4400, 2578, 1272, 1846, 3204, 2454, 2368, 5754, 2366, 2500, 2536, 2200, 2304, 2700, 2166, 2746, 5100, 4400, 3570, 4756, 5434, 5164, 3246, 3448, 4034, 3408, 3757, 3630, 5682, 4500, 6688, 3550, 3926, 5576, 6282, 3013, 3200, 3983, 3764, 5080, 7208, 4860, 5302, 5302, 5302, 1500, 2748, 3660, 2500, 1400, 2000, 3450, 2086, 2632, 3505, 5336, 1665, 4666, 5283, 3286, 3644, 2426, 4220, 3404, 3496, 2536, 4667, 2442, 4604, 3296, 2516, 3422, 3152, 1900, 5666, 3470, 2014, 2870, 2706, 5358, 2784, 3635, 5433, 2120, 1680, 3700, 4350, 2550, 3930, 1700, 2666, 2060, 3258, 5934, 2520, 2358, 2200, 4111, 3000, 5441, 4538, 5700, 4512, 4162, 4150, 3600, 5666, 3420, 8010, 3350, 4430, 3938, 5508, 3300, 4170, 3454, 3910, 4118, 4512, 4310, 4292, 4700, 4666, 4420, 4854, 4500, 3770, 3678, 2302, 4908, 4038, 3300, 3120, 3180, 4170, 2976, 3561, 2944, 3146, 2620, 3358, 2700, 3096, 3306, 3040, 6107, 3251, 4800, 2668, 2925, 3400
#> $ tuitfee_grad_res <dbl> 9366, 8458, 10470, 19140, 7948, 11192, 11506, 9284, 8350, 5918, 16444, 8123, 7994, 7876, 8306, 7689, 7579, 7826, 7830, 7726, 7649, 7853, 8166, 12683, 8475, 8350, 7750, 8684, 42305, 11716, 45591, 8641, 15996, 18450, 13650, 11219, 5510, 17626, 17820, 8872, 9876, 11097, 11543, 19175, 9630, 10428, 9062, 5004, 9004, 10762, 5286, 6490, 16168, 17320, 8440, 8971, 10800, 8776, 19290, 9268, 16343, 8970, 19442, 7797, 18320, 13677, 14583, 7954, 9395, 7243, 7243, 7243, 10357, 9803, 16300, 10438, 9712, 8360, 6078, 10242, 12204, 12236, 12442, 10392, 13608, 11400, 7122, 11887, 7958, 51010, 8666, 20622, 7670, 8478, 8370, 27306, 49886, 10238, 7191, 20718, 29835, 5724, 25818, 16355, 7046, 15408, 13410, 21794, 16764, 16503, 14235, 12778, 7563, 17735, 17483, 8256, 11160, 24600, 7261, 6878, 7659, 9576, 7471, 10668, 8025, 19896, 5554, 49280, 5893, 6090, 5500, 5287, 15920, 16472, 24856, 12140, 17676, 18633, 21722, 13900, 4941, 4650, 38958, 45554, 10690, 10438, 10560, 23308, 32651, 27198, 30176, 21330, 42368, 13782, 12694, 12921, 13347, 12566, 35874, 17200, 20025, 7721, 7288, 5533, 7447, 11606, 7278, 7753, 7124, 10572, 7043, 5924, 7192, 8643, 9136, 42610, 14468, 9679, 13528, 12425, 9510, 14721, 13474, 8902, 8169, 15504, 30634, 14565, 15508, 11184, 10489, 10715, 14898, 35604, 14976, 16676, 13991, 25100, 7178, 12798, 14612, 8558, 9773, 9371, 10463, 9234, 11070, 9876, 12834, 9420, 6890, 19890, 31500, 5776, 8938, 16206, 6608, 6427, 7968, 6109, 8819, 11300, 5623, 26688, 7101, 7525, 6349, 6680, 6277, 7527, 17012, 13724, 10568, 10958, 13143, 11794, 20118, 23238, 16266, 7750, 7420, 9000, 9220, 8762, 11943, 11789, 5673, 4494, 2524, 3552, 8649, 7645, 8961
#> $ tuitfee_grad_nres <dbl> 17496, 14632, 26950, 19140, 15094, 21712, 24176, 19004, 19813, 10544, 16444, 17051, 16922, 16804, 17234, 16617, 16507, 16754, 16758, 16654, 16577, 16781, 17094, 27785, 17403, 17278, 16678, 17612, 42305, 25692, 45591, 12946, 37032, 18450, 13650, 24019, 11726, 17626, 17820, 28657, 24669, 24202, 26697, 19175, 9630, 21126, 24894, 15192, 24502, 26360, 14826, 17866, 37648, 17320, 22890, 8971, 10800, 13978, 19290, 16636, 25297, 16542, 19442, 14205, 18320, 13677, 30369, 12938, 24049, 16256, 16256, 16256, 27961, 20277, 16300, 23134, 9712, 16896, 13609, 10242, 12204, 28380, 25682, 15774, 13608, 16320, 16145, 28822, 14899, 51010, 25640, 20622, 19298, 15264, 13572, 27306, 49886, 10238, 8811, 20718, 29835, 5724, 25818, 29075, 10569, 15408, 13410, 43674, 32940, 33696, 29118, 12778, 7563, 26615, 26363, 12084, 11160, 24600, 17614, 6878, 16529, 24286, 17694, 26184, 8025, 19896, 10234, 49280, 20554, 14428, 19410, 19197, 29210, 21147, 24856, 17513, 17676, 30225, 21722, 19663, 15107, 10354, 38958, 45554, 19280, 19028, 19150, 23308, 32651, 27198, 30176, 21330, 42368, 13782, 24034, 24261, 24687, 23906, 35874, 17200, 20025, 20890, 20179, 16381, 19852, 28817, 20449, 21202, 19824, 25094, 19262, 16181, 17599, 20642, 14642, 42610, 26210, 16411, 30242, 32873, 17502, 25057, 22890, 13402, 22272, 15504, 30634, 22053, 22519, 16442, 15497, 10715, 20994, 35604, 21072, 22526, 20015, 25100, 13514, 27408, 27870, 15491, 23753, 23627, 19247, 23346, 11070, 25994, 31252, 21060, 6890, 19890, 31500, 13120, 18082, 16206, 13952, 13771, 16128, 13452, 17316, 21518, 13452, 26688, 22700, 14869, 7028, 6680, 19586, 23902, 40076, 32402, 21204, 19930, 25271, 26279, 20118, 23238, 28314, 13402, 17910, 23238, 18351, 17893, 25269, 24826, 14313, 4494, 6642, 3552, 17577, 16573, 31216
#> $ coa_grad_res <dbl> 22886, 21606, 28836, 35488, 20119, 32096, 26533, 25618, 23832, 21167, 34888, 26725, 22910, 26095, 23936, 25211, 24521, 26530, 25920, 25468, 26353, 22993, 25108, 30126, 25217, 25514, 26498, 27390, 59733, 23969, 61446, 25699, 31932, 35600, 28044, 26289, 25177, 37766, 38420, 24758, 26963, 29878, 27611, 47810, 25582, 25428, 21716, 20784, 24832, 23752, 16738, 21942, 33049, 38102, 22644, 21961, 19178, 23415, 36145, 28036, 32253, 23532, 33742, 23274, 37669, 25797, 28810, 20773, 23827, 19415, 19415, 19415, 23315, 22282, 32894, 24198, 25057, 23193, 22422, 19952, 23054, 28680, 27658, 26070, 29352, 23420, 26063, 34239, 21877, 67114, 22030, 35372, 21850, 26899, 23722, 40456, 67706, 26038, 22103, 39048, 44725, 19560, 41782, 27333, 17360, 23514, 27436, 36168, 29992, 32587, 27110, 33836, 18111, 30312, 28447, 20386, 23338, 37046, 20761, 20072, 22429, 25974, 23401, 26348, 19471, 35184, 18976, 69264, 19876, 19448, 21670, 21645, 34746, 32379, 38983, 29980, 36376, 40930, 39030, 31422, 18947, 19420, 56906, 68824, 31069, 30817, 30939, 28708, 48335, 42388, 59676, 36980, 63016, 25554, 25730, 24643, 29289, 31702, 54196, 35509, 39815, 20087, 21453, 16429, 20220, 28670, 21797, 19989, 22927, 24731, 21375, 18933, 21959, 20921, 25630, 60008, 33736, 25949, 29212, 28235, 25514, 28743, 28882, 22627, 24596, 29102, 45186, 32555, 31382, 25953, 25485, 23415, 31913, 53480, 28938, 35946, 30571, 36948, 22978, 28472, 26076, 23207, 25572, 24113, 25543, 23182, 24520, 23976, 30336, 21750, 25550, 33800, 47950, 18894, 26813, 28578, 19658, 19941, 19958, 21137, 22947, 26342, 20627, 44438, 22325, 22226, 20785, 19440, 18737, 22373, 30514, 32018, 26631, 23863, 30347, 26815, 37287, 34389, 35277, 20144, 20920, 20860, 20564, 20062, 26685, 25925, 20233, 18760, 19104, 18052, 25907, 27359, 23233
#> $ coa_grad_nres <dbl> 31016, 27780, 45316, 35488, 27265, 42616, 39203, 35338, 35295, 25793, 34888, 35653, 31838, 35023, 32864, 34139, 33449, 35458, 34848, 34396, 35281, 31921, 34036, 45228, 34145, 34442, 35426, 36318, 59733, 37945, 61446, 30004, 52968, 35600, 28044, 39089, 31393, 37766, 38420, 44543, 41756, 42983, 42765, 47810, 25582, 36126, 37548, 30972, 40330, 39350, 26278, 33318, 54529, 38102, 37094, 21961, 19178, 28617, 36145, 35404, 41207, 31104, 33742, 29682, 37669, 25797, 44596, 25757, 38481, 28428, 28428, 28428, 40919, 32756, 32894, 36894, 25057, 31729, 29953, 19952, 23054, 44824, 40898, 31452, 29352, 28340, 35086, 51174, 28818, 67114, 39004, 35372, 33478, 33685, 28924, 40456, 67706, 26038, 23723, 39048, 44725, 19560, 41782, 40053, 20883, 23514, 27436, 58048, 46168, 49780, 41993, 33836, 18111, 39192, 37327, 24214, 23338, 37046, 31114, 20072, 31299, 40684, 33624, 41864, 19471, 35184, 23656, 69264, 34537, 27786, 35580, 35555, 48036, 37054, 38983, 35353, 36376, 52522, 39030, 37185, 29113, 25124, 56906, 68824, 39659, 39407, 39529, 28708, 48335, 42388, 59676, 36980, 63016, 25554, 37070, 35983, 40629, 43042, 54196, 35509, 39815, 33256, 34344, 27277, 32625, 45881, 34968, 33438, 35627, 39253, 33594, 29190, 32366, 32920, 31136, 60008, 45478, 32681, 45926, 48683, 33506, 39079, 38298, 27127, 38699, 29102, 45186, 40043, 38393, 31211, 30493, 23415, 38009, 53480, 35034, 41796, 36595, 36948, 29314, 43082, 39334, 30140, 39552, 38369, 34327, 37294, 24520, 40094, 48754, 33390, 25550, 33800, 47950, 26238, 35957, 28578, 27002, 27285, 28118, 28480, 31444, 36560, 28456, 44438, 37924, 29570, 21464, 19440, 32046, 38748, 53578, 50696, 37267, 32835, 42475, 41300, 37287, 34389, 47325, 25796, 31410, 35098, 29695, 29193, 40011, 38962, 28873, 18760, 23222, 18052, 34835, 36287, 45488
# investigate data structure
# one observation per opeid6
df_socialwork %>% group_by(opeid6) %>% summarise(n_per_key=n()) %>% ungroup() %>% count(n_per_key)
#> # A tibble: 1 x 2
#> n_per_key n
#> <int> <int>
#> 1 1 253
# also, one observation per unitid
df_socialwork %>% group_by(unitid) %>% summarise(n_per_key=n()) %>% ungroup() %>% count(n_per_key)
#> # A tibble: 1 x 2
#> n_per_key n
#> <int> <int>
#> 1 1 253
##### create data frame that only contains observations for MAs in business
#particularly the degree "Business Administration, Management and Operations", which is associated with general MBA programs
#df_score_ipeds %>% filter(cipdig2=="52") %>% count(cipcode)
#df_score_ipeds %>% filter(cipdig2=="52") %>% count(cipdesc)
df_mba <- df_score_ipeds %>%
filter(cipcode=='5202') %>%
# remove observations with missing values of cost of attendance (better for teaching concepts)
filter(!is.na(coa_grad_res))
df_mba %>% glimpse()
#> Rows: 665
#> Columns: 36
#> $ opeid6 <chr> "001002", "001052", "025034", "001055", "001051", "001009", "001003", "001004", "001016", "001036", "001047", "001063", "001061", "001081", "001083", "001082", "001101", "001108", "001090", "001089", "001092", "001097", "001100", "001107", "001117", "001125", "001133", "001143", "007993", "001157", "001142", "001144", "001146", "001141", "001147", "001137", "001138", "001139", "001140", "001153", "001150", "001313", "001314", "001315", "001316", "001317", "001164", "020705", "001196", "001253", "001205", "001183", "001149", "001216", "001215", "001243", "011460", "001179", "001252", "001329", "010149", "001262", "001322", "001151", "010395", "001154", "001325", "001155", "001326", "001302", "001156", "001328", "001343", "001345", "004508", "004509", "001370", "009401", "001350", "001371", "001363", "001374", "001416", "001378", "001417", "001385", "001422", "001397", "001402", "001403", "001409", "001406", "001380", "001431", "007948", "001434", "001443", "001444", "001460", "001466", "001505", "003954", "001479", "001480", "001481", "001469", "009635", "001488", "001535", "001495", "021519", "001536", "009841", "001509", "008849", "001515", "001526", "001537", "001468", "001531", "001521", "001538", "003955", "001544", "001556", "008976", "001561", "001564", "001569", "001573", "001602", "001572", "001598", "001588", "001599", "001601", "001605", "001610", "007279", "001616", "001620", "001626", "001624", "001634", "001641", "001666", "001671", "001674", "001676", "009145", "001776", "001767", "001692", "001700", "001707", "001710", "001722", "001733", "001734", "001735", "001737", "001739", "001693", "001741", "001746", "001748", "001749", "001750", "001664", "001768", "001758", "001759", "001780", "001785", "001787", "001788", "001800", "001804", "001808", "001807", "001811", "001822", "001832", "001842", "001891", "001869", "001892", "001880", "001889", "001893", "001903", "001927", "001915", "001918", "001948", "001939", "001928", "007032", "001926", "001943", "001940", "001949", "001950", "001954", "001959", "001962", "001975", "002002", "002010", "002008", "002017", "002015", "002005", "002020", "002024", "002025", "002031", "002029", "002053", "002051", "002054", "002052", "002102", "002062", "002072", "002076", "002077", "002078", "011644", "002103", "002083", "002086", "002091", "002114", "002117", "002118", "002122", "002124", "002128", "002130", "002133", "002183", "021829", "002139", "002143", "002184", "002161", "002221", "002222", "002199", "002188", "002208", "002211", "002210", "002218", "002226", "002233", "002190", "002238", "002243", "002249", "002323", "002259", "002262", "002266", "002279", "002325", "002290", "002326", "002327", "002307", "002314", "002316", "002318", "002329", "002330", "002334", "009058", "002347", "002354", "010374", "003969", "002371", "002377", "002380", "002345", "002342", "002375", "002394", "002396", "002397", "002403", "002410", "002440", "002424", "002415", "002423", "002441", "002447", "002449", "002454", "002461", "002463", "002464", "002480", "007540", "002496", "002498", "002499", "002506", "002501", "002503", "002520", "002521", "002525", "002536", "009743", "002539", "002554", "002565", "002540", "002566", "002569", "002568", "002575", "002579", "002580", "002591", "002586", "002598", "002599", "002607", "002610", "002608", "002609", "002613", "002622", "002616", "002617", "002621", "009344", "002628", "002629", "002638", "002639", "009345", "021922", "002625", "002651", "002653", "002663", "002657", "002650", "002664", "002666", "002668", "002681", "002699", "009769", "002707", "002711", "007273", "002687", "007022", "002712", "002713", "002722", "002732", "002737", "002744", "002748", "002751", "002758", "002765", "002772", "002775", "002778", "002703", "020662", "002785", "002782", "002790", "002791", "002805", "002806", "002810", "002817", "002705", "002825", "002821", "002823", "002835", "002836", "002837", "002838", "002842", "002846", "002848", "010286", "002853", "002882", "010142", "002883", "002899", "002906", "002913", "002923", "002927", "002928", "002929", "002941", "002948", "002905", "002974", "002975", "002976", "002950", "002972", "002984", "002954", "002955", "002957", "002978", "002985", "002981", "002992", "002994", "003005", "002997", "003123", "003012", "003014", "003018", "003023", "003024", "003125", "003032", "003127", "003045", "003050", "003051", "003066", "003069", "003072", "003077", "007085", "003033", "003035", "003090", "003100", "003121", "003131", "010923", "003134", "003135", "003078", "003144", "003145", "003151", "003149", "003152", "003161", "003170", "003166", "003184", "003179", "003181", "003185", "003193", "003194", "003208", "003210", "003223", "003212", "003216", "003224", "003219", "003986", "003233", "003315", "003241", "003316", "003303", "003244", "003318", "003252", "003256", "003258", "003259", "003266", "003267", "003270", "003275", "003277", "003287", "003288", "003289", "003290", "003296", "003988", "003329", "003378", "003357", "003360", "003366", "003384", "003362", "003326", "003327", "003371", "003388", "003391", "003328", "003313", "003394", "003399", "003402", "003404", "003406", "003414", "003411", "003418", "003419", "003422", "003428", "003425", "003441", "003448", "003451", "003456", "003469", "003474", "003478", "003479", "003481", "003482", "003485", "003486", "003487", "003496", "003500", "003502", "003509", "003510", "003529", "003530", "003531", "003522", "003523", "003527", "003528", "003537", "003541", "003545", "003557", "011161", "003560", "003651", "031703", "003565", "003576", "011711", "003612", "013231", "003652", "003578", "003581", "009651", "003584", "003588", "003592", "003594", "003598", "003630", "003604", "003621", "003654", "003606", "003623", "003613", "003616", "003624", "003615", "003631", "003639", "003632", "003656", "003658", "009741", "003661", "011163", "003636", "010115", "003642", "003644", "003646", "003663", "003665", "003670", "003678", "003677", "004027", "003675", "003680", "003681", "003684", "003692", "003696", "003705", "030913", "003708", "003749", "003714", "003721", "020530", "003720", "003746", "003724", "003728", "003737", "003754", "003735", "003745", "013022", "003775", "003778", "003783", "003785", "003794", "003790", "003800", "003798", "003802", "003804", "003812", "003827", "003832", "003837", "003838", "003842", "003848", "003854", "003861", "003863", "003911", "003917", "003920", "003896", "003921", "003923", "003932", "025875", "003941", "011719", "001825", "006942", "041618", "030113", "030375", "032603", "033394", "032553", "039803", "041425", "001579"
#> $ unitid <dbl> 100654, 100663, 100690, 100706, 100751, 100858, 101189, 101709, 101879, 102049, 102368, 102614, 102669, 104151, 104179, 105330, 106245, 106397, 106458, 106467, 106704, 107044, 107141, 107983, 109785, 110361, 110413, 110422, 110486, 110495, 110510, 110529, 110538, 110547, 110556, 110565, 110574, 110583, 110592, 110608, 110617, 110644, 110653, 110662, 110671, 110680, 111948, 112075, 113698, 114813, 115083, 115728, 115755, 117140, 117627, 119173, 119605, 120184, 120537, 120883, 121150, 121309, 121691, 122409, 122436, 122597, 122612, 122755, 122931, 123554, 123572, 123961, 125897, 126182, 126562, 126580, 126614, 126669, 126818, 127060, 127918, 128498, 128744, 128771, 129020, 129242, 129525, 129941, 130226, 130253, 130314, 130493, 130776, 130943, 131113, 131159, 131450, 131469, 131876, 132471, 132657, 132903, 133553, 133650, 133669, 133881, 133951, 134079, 134130, 134945, 135081, 135726, 136172, 136215, 136330, 136950, 137032, 137351, 137476, 137546, 137564, 137847, 138354, 138716, 139199, 139311, 139366, 139658, 139755, 139764, 139861, 139931, 139959, 140818, 141264, 141334, 141486, 141574, 141644, 142115, 142276, 142285, 142461, 143118, 143358, 144351, 144740, 144892, 144962, 145336, 145600, 145619, 145813, 146339, 146612, 146719, 147013, 147536, 147660, 147679, 147703, 147767, 147776, 147828, 148335, 148405, 148487, 148496, 148584, 148627, 149222, 149231, 149772, 150066, 150145, 150163, 150677, 151263, 151306, 151324, 151388, 151801, 152336, 152600, 153278, 153603, 153658, 154013, 154235, 154493, 154688, 155025, 155061, 155089, 155317, 155335, 155399, 155520, 155681, 155812, 155900, 156082, 156125, 156286, 156365, 156541, 157377, 157951, 159391, 159647, 159717, 159939, 159966, 159993, 160612, 160621, 160658, 160755, 161253, 161518, 161554, 161563, 161873, 162007, 162584, 162760, 162928, 163046, 163204, 163286, 163453, 163462, 163851, 164447, 164492, 164562, 164632, 164739, 164924, 164988, 165015, 165024, 165167, 165334, 165529, 165820, 166513, 166629, 166638, 167358, 167729, 167783, 167899, 167987, 168005, 168254, 168421, 168430, 168740, 169248, 169479, 169716, 169798, 169983, 170037, 170675, 170976, 171100, 171137, 171146, 171571, 172051, 172264, 172334, 172644, 172699, 173045, 173160, 173328, 173665, 174020, 174066, 174491, 174783, 174817, 174914, 175005, 175078, 175272, 175342, 175421, 175616, 175856, 176017, 176044, 176053, 176080, 176372, 176479, 176628, 176965, 177214, 177339, 177418, 177968, 178244, 178624, 178721, 179043, 179159, 179557, 179566, 179867, 179894, 179964, 180489, 180814, 180948, 181394, 181464, 181604, 181783, 182281, 182290, 182795, 182980, 183026, 183080, 183211, 183910, 183974, 184603, 184612, 184773, 184782, 185129, 185262, 185572, 185590, 185828, 186201, 186283, 186380, 186432, 186867, 186876, 187046, 187444, 187648, 187897, 187985, 188030, 188182, 188304, 188429, 188641, 189705, 190044, 190114, 190150, 190415, 190512, 190549, 190637, 190716, 190761, 191241, 191649, 191931, 192192, 192323, 192448, 192703, 192819, 193016, 193292, 193353, 193399, 193654, 193900, 194091, 194161, 194310, 194958, 195003, 195128, 195164, 195234, 195544, 195720, 195809, 196060, 196079, 196088, 196097, 196130, 196176, 196194, 196264, 196291, 196413, 196592, 197045, 197197, 197869, 198136, 198464, 198516, 198543, 198561, 198835, 199032, 199102, 199120, 199139, 199148, 199157, 199193, 199218, 199281, 199306, 199412, 199847, 199962, 200004, 200217, 200253, 200280, 200332, 200800, 201104, 201195, 201441, 201548, 201645, 201885, 202134, 202480, 202763, 203368, 203517, 203580, 203757, 203775, 204024, 204194, 204200, 204617, 204796, 204857, 206048, 206084, 206279, 206349, 206437, 206604, 206622, 206695, 206835, 206862, 206941, 207263, 207388, 207458, 207500, 207847, 207865, 207971, 208646, 208822, 209409, 209542, 209551, 209612, 209807, 209825, 210146, 210739, 210775, 211158, 211352, 211361, 211431, 211556, 211644, 211981, 212054, 212106, 212133, 212601, 212656, 212832, 212984, 213020, 213367, 213507, 213543, 213598, 213826, 214272, 214777, 215062, 215442, 215691, 215743, 215929, 215947, 216010, 216038, 216339, 216597, 216694, 216764, 216852, 216931, 217059, 217165, 217235, 217402, 217484, 217536, 217633, 217688, 217776, 217819, 217882, 218441, 218663, 218724, 218964, 219383, 219471, 219602, 219709, 219806, 219833, 219949, 219976, 220075, 220516, 220613, 220631, 220862, 220978, 221740, 221759, 221768, 221838, 221847, 221953, 221971, 222178, 222831, 223232, 224004, 224147, 224226, 224323, 224545, 224554, 225399, 225414, 225432, 225502, 225511, 225627, 226091, 226152, 226231, 226471, 226833, 227216, 227331, 227526, 227757, 227845, 227863, 227881, 228149, 228246, 228325, 228431, 228459, 228529, 228705, 228723, 228769, 228778, 228787, 228796, 228802, 228875, 229027, 229063, 229115, 229179, 229780, 229814, 230038, 230603, 230728, 230737, 230764, 230782, 230807, 230852, 230995, 231174, 231624, 231651, 232043, 232186, 232265, 232423, 232557, 232609, 232681, 232706, 232982, 233541, 233921, 234030, 234076, 234915, 235097, 235316, 236133, 236230, 236452, 236595, 236939, 236948, 237011, 237066, 237367, 238032, 238193, 238430, 238458, 238616, 238661, 238980, 239080, 239105, 240107, 240268, 240365, 240453, 240462, 240471, 240727, 241739, 243346, 243601, 243780, 245953, 262086, 366711, 367884, 409698, 433387, 433660, 441937, 459727, 482149
#> $ instnm <chr> "Alabama A & M University", "University of Alabama at Birmingham", "Amridge University", "University of Alabama in Huntsville", "The University of Alabama", "Auburn University", "Faulkner University", "University of Montevallo", "University of North Alabama", "Samford University", "Troy University", "University of Alaska Fairbanks", "Alaska Pacific University", "Arizona State University-Tempe", "University of Arizona", "Northern Arizona University", "University of Arkansas at Little Rock", "University of Arkansas", "Arkansas State University-Main Campus", "Arkansas Tech University", "University of Central Arkansas", "Harding University", "John Brown University", "Southern Arkansas University Main Campus", "Azusa Pacific University", "California Baptist University", "California Lutheran University", "California Polytechnic State University-San Luis Obispo", "California State University-Bakersfield", "California State University-Stanislaus", "California State University-San Bernardino", "California State Polytechnic University-Pomona", "California State University-Chico", "California State University-Dominguez Hills", "California State University-Fresno", "California State University-Fullerton", "California State University-East Bay", "California State University-Long Beach", "California State University-Los Angeles", "California State University-Northridge", "California State University-Sacramento", "University of California-Davis", "University of California-Irvine", "University of California-Los Angeles", "University of California-Riverside", "University of California-San Diego", "Chapman University", "Concordia University-Irvine", "Dominican University of California", "Fresno Pacific University", "Golden Gate University-San Francisco", "Holy Names University", "Humboldt State University", "University of La Verne", "La Sierra University", "Mount Saint Mary's University", "National University", "Notre Dame de Namur University", "Hope International University", "University of the Pacific", "Pepperdine University", "Point Loma Nazarene University", "University of Redlands", "San Diego State University", "University of San Diego", "San Francisco State University", "University of San Francisco", "San Jose State University", "Santa Clara University", "Saint Mary's College of California", "Sonoma State University", "University of Southern California", "Woodbury University", "Adams State University", "University of Colorado Denver/Anschutz Medical Campus", "University of Colorado Colorado Springs", "University of Colorado Boulder", "Colorado Christian University", "Colorado State University-Fort Collins", "University of Denver", "Regis University", "Albertus Magnus College", "University of Bridgeport", "Central Connecticut State University", "University of Connecticut", "Fairfield University", "University of Hartford", "University of New Haven", "Quinnipiac University", "Sacred Heart University", "University of Saint Joseph", "Southern Connecticut State University", "Western Connecticut State University", "University of Delaware", "Wilmington University", "American University", "Gallaudet University", "George Washington University", "Trinity Washington University", "Barry University", "Lynn University", "University of Central Florida", "Embry-Riddle Aeronautical University-Daytona Beach", "Florida Agricultural and Mechanical University", "Florida Atlantic University", "Florida Institute of Technology", "Florida International University", "Florida Southern College", "University of Florida", "Jacksonville University", "Keiser University-Ft Lauderdale", "University of Miami", "University of North Florida", "Nova Southeastern University", "Palm Beach Atlantic University", "Rollins College", "Saint Leo University", "University of South Florida-Main Campus", "St. Thomas University", "Stetson University", "Southeastern University", "The University of Tampa", "The University of West Florida", "Albany State University", "Brenau University", "Clayton State University", "Columbus State University", "Emory University", "Georgia Institute of Technology-Main Campus", "Georgia Southwestern State University", "Georgia College & State University", "Georgia Southern University", "University of Georgia", "Piedmont College", "Valdosta State University", "University of West Georgia", "Chaminade University of Honolulu", "University of Hawaii at Manoa", "Hawaii Pacific University", "Boise State University", "Idaho State University", "University of Idaho", "Northwest Nazarene University", "Aurora University", "Bradley University", "Concordia University-Chicago", "DePaul University", "Eastern Illinois University", "Elmhurst College", "Governors State University", "University of Illinois at Chicago", "Benedictine University", "Illinois State University", "Judson University", "Lewis University", "Loyola University Chicago", "McKendree University", "National Louis University", "North Central College", "North Park University", "Northern Illinois University", "Northwestern University", "Northeastern Illinois University", "Olivet Nazarene University", "Robert Morris University Illinois", "Rockford University", "Roosevelt University", "Dominican University", "University of St Francis", "Saint Xavier University", "Southern Illinois University-Carbondale", "Southern Illinois University-Edwardsville", "Western Illinois University", "Anderson University", "Bethel University", "Butler University", "Grace College and Theological Seminary", "University of Indianapolis", "University of Southern Indiana", "Indiana State University", "Indiana University-East", "Indiana Wesleyan University-Marion", "University of Saint Francis-Fort Wayne", "Valparaiso University", "University of Dubuque", "Iowa State University", "University of Iowa", "Mount Mercy University", "Saint Ambrose University", "Upper Iowa University", "Baker University", "Emporia State University", "Fort Hays State University", "Friends University", "University of Kansas", "Newman University", "Kansas State University", "MidAmerica Nazarene University", "Pittsburg State University", "University of Saint Mary", "Southwestern College", "Washburn University", "Wichita State University", "Bellarmine University", "Campbellsville University", "University of the Cumberlands", "Midway University", "Western Kentucky University", "Louisiana State University and Agricultural & Mechanical College", "Louisiana Tech University", "McNeese State University", "University of New Orleans", "Nicholls State University", "University of Louisiana at Monroe", "Southeastern Louisiana University", "Southern University and A & M College", "University of Louisiana at Lafayette", "Tulane University of Louisiana", "University of Maine", "Saint Joseph's College of Maine", "University of Southern Maine", "Thomas College", "University of Baltimore", "Bowie State University", "Frostburg State University", "Hood College", "Johns Hopkins University", "Loyola University Maryland", "University of Maryland Global Campus", "University of Maryland-College Park", "Morgan State University", "Mount St. Mary's University", "Salisbury University", "American International College", "Anna Maria College", "Assumption College", "Bay Path University", "Bentley University", "Boston College", "Boston University", "Brandeis University", "Bridgewater State University", "Cambridge College", "Clark University", "Curry College", "Fitchburg State University", "University of Massachusetts-Lowell", "University of Massachusetts-Amherst", "University of Massachusetts-Boston", "Northeastern University", "Salem State University", "Simmons University", "Springfield College", "University of Massachusetts-Dartmouth", "Suffolk University", "Western New England University", "Worcester Polytechnic Institute", "Worcester State University", "Andrews University", "Central Michigan University", "Davenport University", "University of Detroit Mercy", "Eastern Michigan University", "Kettering University", "Cornerstone University", "Lawrence Technological University", "University of Michigan-Ann Arbor", "Michigan State University", "University of Michigan-Dearborn", "University of Michigan-Flint", "Oakland University", "Saginaw Valley State University", "Siena Heights University", "Spring Arbor University", "Wayne State University", "Western Michigan University", "Augsburg University", "Bethel University", "Concordia University-Saint Paul", "Hamline University", "Metropolitan State University", "University of Minnesota-Twin Cities", "University of Northwestern-St Paul", "Saint Cloud State University", "Saint Mary's University of Minnesota", "University of St Thomas", "St Catherine University", "Southwest Minnesota State University", "Winona State University", "Alcorn State University", "Belhaven University", "Delta State University", "Jackson State University", "University of Mississippi", "Mississippi Valley State University", "Mississippi College", "Mississippi State University", "University of Southern Mississippi", "William Carey University", "Avila University", "University of Central Missouri", "Drury University", "Evangel University", "Fontbonne University", "Lindenwood University", "Missouri Baptist University", "Northwest Missouri State University", "Park University", "Rockhurst University", "Saint Louis University", "Southeast Missouri State University", "Missouri State University-Springfield", "Washington University in St Louis", "Webster University", "William Woods University", "The University of Montana", "Bellevue University", "Chadron State College", "University of Nebraska at Omaha", "University of Nebraska-Lincoln", "College of Saint Mary", "Wayne State College", "University of Nevada-Las Vegas", "University of Nevada-Reno", "Franklin Pierce University", "New England College", "Southern New Hampshire University", "Plymouth State University", "Rivier University", "Caldwell University", "Centenary University", "Fairlei...
#> $ control <dbl+lbl> 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 2, 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 1, 2, 1, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 2, 2, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, 2, 2, 2, 1, 2, 1, 1, 2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 2, 2, 2, 2, 1, 1, 2, 1, 2, 1, 2, 1, 2, 2, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 1, 1, 1, 1, 2, 1, 2, 2, 1, 2, 2, 2, 1, 2, 1, 2, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 2, 2, 2, 2, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 1, 1, 2, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 2, 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 2, 2, 1, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 1, 2, 1, 2, 2, 2, 1, 2, 1, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 1, 1, 2, 1, 2, 1, 2, 2, 1, 2, 1, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 2, 2, 1, 1, 2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 2, 2, 1, 2, 1, 2, 2, 1, 2, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 2, 1, 2, 1, 2, 1, 1, 2, 1
#> $ ccbasic <dbl+lbl> 18, 15, 20, 16, 15, 15, 19, 19, 18, 17, 18, 16, 20, 15, 15, 16, 16, 15, 16, 18, 17, 17, 19, 18, 16, 18, 18, 18, 18, 18, 18, 18, 18, 18, 17, 18, 18, 18, 18, 18, 18, 15, 15, 15, 15, 15, 16, 18, 19, 18, 18, 19, 19, 17, 19, 18, 18, 19, 19, 17, 17, 18, 18, 16, 16, 18, 17, 18, 17, 18, 18, 15, 19, 18, 15, 16, 15, 19, 15, 16, 17, 19, 17, 18, 15, 18, 17, 18, 17, 17, 17, 18, 19, 15, 17, 16, 16, 15, 19, 17, 18, 15, 19, 16, 16, 16, 15, 19, 15, 18, 17, 15, 17, 16, 17, 18, 18, 15, 18, 18, 19, 18, 18, 19, 18, 19, 18, 15, 15, 19, 18, 16, 15, 18, 17, 17, 18, 15, 18, 16, 16, 16, 18, 17, 18, 18, 16, 18, 18, 18, 15, 17, 16, 20, 18, 16, 18, 17, 19, 18, 16, 15, 18, 18, 19, 20, 17, 18, 17, 18, 16, 17, 18, 19, 20, 18, 19, 17, 18, 17, 20, 20, 18, 17, 19, 15, 15, 19, 18, 18, 17, 18, 18, 18, 15, 18, 15, 19, 18, 19, 19, 17, 16, 17, 18, 17, 20, 17, 15, 16, 18, 16, 18, 17, 18, 18, 16, 15, 16, 18, 18, 20, 18, 18, 18, 18, 15, 18, 18, 15, 16, 19, 18, 18, 19, 19, 18, 18, 15, 15, 15, 18, 18, 16, 19, 18, 16, 15, 16, 15, 18, 17, 18, 16, 18, 17, 16, 18, 17, 16, 18, 17, 16, 19, 19, 18, 15, 15, 18, 17, 16, 18, 20, 18, 15, 16, 18, 17, 18, 18, 17, 15, 19, 18, 18, 17, 17, 19, 20, 19, 18, 18, 16, 15, 20, 17, 15, 15, 17, 19, 18, 19, 19, 18, 17, 18, 18, 18, 18, 16, 18, 17, 15, 18, 17, 16, 18, 19, 16, 15, 19, 19, 15, 15, 19, 18, 18, 18, 18, 19, 19, 18, 19, 19, 16, 18, 18, 18, 16, 15, 19, 18, 15, 18, 16, 18, 19, 18, 18, 18, 15, 16, 19, 18, 17, 18, 18, 16, 18, 15, 15, 18, 18, 18, 17, 20, 16, 17, 18, 19, 18, 17, 18, 18, 18, 18, 19, 20, 16, 15, 18, 18, 17, 18, 16, 17, 19, 18, 19, 17, 17, 15, 15, 15, 15, 18, 18, 18, 18, 20, 15, 17, 18, 19, 18, 17, 16, 17, 19, 17, 18, 20, 16, 15, 16, 16, 18, 15, 16, 18, 18, 18, 16, 17, 18, 17, 19, 16, 16, 16, 18, 18, 16, 19, 15, 15, 16, 16, 17, 19, 16, 19, 20, 19, 16, 19, 18, 18, 15, 16, 18, 16, 17, 19, 19, 16, 18, 18, 19, 18, 18, 18, 15, 17, 15, 18, 18, 16, 19, 17, 19, 15, 15, 17, 16, 19, 18, 18, 19, 18, 18, 18, 18, 17, 18, 20, 15, 16, 18, 17, 19, 19, 18, 17, 18, 20, 16, 19, 18, 18, 15, 15, 18, 19, 18, 18, 19, 18, 18, 15, 16, 19, 18, 17, 17, 20, 19, 18, 18, 16, 18, 19, 19, 18, 18, 15, 20, 15, 18, 18, 19, 16, 18, 17, 17, 18, 19, 17, 16, 18, 19, 17, 16, 17, 17, 15, 20, 16, 16, 19, 17, 18, 18, 16, 18, 16, 17, 18, 19, 17, 18, 18, 18, 18, 15, 17, 17, 18, 19, 18, 18, 15, 17, 18, 15, 18, 18, 17, 18, 16, 20, 17, 16, 18, 16, 15, 15, 15, 15, 15, 17, 16, 16, 16, 15, 17, 18, 18, 16, 18, 16, 20, 15, 18, 18, 18, 18, 16, 16, 17, 19, 15, 16, 18, 17, 19, 19, 18, 16, 17, 15, 15, 15, 18, 18, 17, 19, 19, 19, 17, 15, 15, 18, 19, 20, 15, 19, 17, 20, 17, 17, 18, 19, 16, 18, 19, 18, 15, 18, 19, 16, 18, 18, 17, 15, 19, 17, 18, 20, 19, 18, 18, 19, 18, 17
#> $ stabbr <chr> "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AK", "AK", "AZ", "AZ", "AZ", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "AR", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CA", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CO", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "CT", "DE", "DE", "DC", "DC", "DC", "DC", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "FL", "GA", "GA", "GA", "GA", "GA", "GA", "GA", "GA", "GA", "GA", "GA", "GA", "GA", "HI", "HI", "HI", "ID", "ID", "ID", "ID", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IL", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IA", "IA", "IA", "IA", "IA", "IA", "KS", "KS", "KS", "KS", "KS", "KS", "KS", "KS", "KS", "KS", "KS", "KS", "KS", "KY", "KY", "KY", "KY", "KY", "LA", "LA", "LA", "LA", "LA", "LA", "LA", "LA", "LA", "LA", "ME", "ME", "ME", "ME", "MD", "MD", "MD", "MD", "MD", "MD", "MD", "MD", "MD", "MD", "MD", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MA", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MI", "MN", "MN", "MN", "MN", "MN", "MN", "MN", "MN", "MN", "MN", "MN", "MN", "MN", "MS", "MS", "MS", "MS", "MS", "MS", "MS", "MS", "MS", "MS", "MO", "MO", "MO", "MO", "MO", "MO", "MO", "MO", "MO", "MO", "MO", "MO", "MO", "MO", "MO", "MO", "MT", "NE", "NE", "NE", "NE", "NE", "NE", "NV", "NV", "NH", "NH", "NH", "NH", "NH", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NJ", "NM", "NM", "NM", "NM", "NM", "NM", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NY", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "NC", "ND", "ND", "ND", "ND", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OH", "OK", "OK", "OK", "OK", "OK", "OK", "OK", "OK", "OK", "OK", "OR", "OR", "OR", "OR", "OR", "OR", "OR", "OR", "OR", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "PA", "RI", "RI", "RI", "RI", "RI", "SC", "SC", "SC", "SC", "SC", "SC", "SC", "SC", "SC", "SD", "SD", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TN", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "TX", "UT", "UT", "UT", "UT", "UT", "UT", "UT", "VT", "VT", "VT", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "WA", "WA", "WA", "WA", "WA", "WA", "WA", "WA", "WA", "WA", "WA", "WV", "WV", "WI", "WI", "WI", "WI", "WI", "WI", "WI", "WI", "WI", "WI", "WI", "WI", "WI", "WI", "WY", "PR", "PR", "PR", "IN", "OK", "CA", "CA", "FL", "CA", "UT", "FL", "CA", "CA", "GA"
#> $ region <dbl+lbl> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 8, 8, 6, 6, 6, 5, 5, 5, 5, 5, 5, 5, 5, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 7, 7, 7, 7, 7, 7, 7, 7, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 8, 8, 8, 7, 7, 7, 7, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 7, 4, 4, 4, 4, 4, 4, 8, 8, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 6, 6, 6, 6, 6, 6, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 8, 8, 8, 8, 8, 8, 8, 8, 8, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 5, 5, 5, 5, 5, 5, 5, 5, 5, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 1, 1, 1, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 5, 5, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 7, 9, 9, 9, 3, 6, 8, 8, 5, 8, 7, 5, 8, 8, 5
#> $ city <chr> "Normal", "Birmingham", "Montgomery", "Huntsville", "Tuscaloosa", "Auburn", "Montgomery", "Montevallo", "Florence", "Birmingham", "Troy", "Fairbanks", "Anchorage", "Tempe", "Tucson", "Flagstaff", "Little Rock", "Fayetteville", "Jonesboro", "Russellville", "Conway", "Searcy", "Siloam Springs", "Magnolia", "Azusa", "Riverside", "Thousand Oaks", "San Luis Obispo", "Bakersfield", "Turlock", "San Bernardino", "Pomona", "Chico", "Carson", "Fresno", "Fullerton", "Hayward", "Long Beach", "Los Angeles", "Northridge", "Sacramento", "Davis", "Irvine", "Los Angeles", "Riverside", "La Jolla", "Orange", "Irvine", "San Rafael", "Fresno", "San Francisco", "Oakland", "Arcata", "La Verne", "Riverside", "Los Angeles", "La Jolla", "Belmont", "Fullerton", "Stockton", "Malibu", "San Diego", "Redlands", "San Diego", "San Diego", "San Francisco", "San Francisco", "San Jose", "Santa Clara", "Moraga", "Rohnert Park", "Los Angeles", "Burbank", "Alamosa", "Denver", "Colorado Springs", "Boulder", "Lakewood", "Fort Collins", "Denver", "Denver", "New Haven", "Bridgeport", "New Britain", "Storrs", "Fairfield", "West Hartford", "West Haven", "Hamden", "Fairfield", "West Hartford", "New Haven", "Danbury", "Newark", "New Castle", "Washington", "Washington", "Washington", "Washington", "Miami", "Boca Raton", "Orlando", "Daytona Beach", "Tallahassee", "Boca Raton", "Melbourne", "Miami", "Lakeland", "Gainesville", "Jacksonville", "Fort Lauderdale", "Coral Gables", "Jacksonville", "Fort Lauderdale", "West Palm Beach", "Winter Park", "Saint Leo", "Tampa", "Miami Gardens", "DeLand", "Lakeland", "Tampa", "Pensacola", "Albany", "Gainesville", "Morrow", "Columbus", "Atlanta", "Atlanta", "Americus", "Milledgeville", "Statesboro", "Athens", "Demorest", "Valdosta", "Carrollton", "Honolulu", "Honolulu", "Honolulu", "Boise", "Pocatello", "Moscow", "Nampa", "Aurora", "Peoria", "River Forest", "Chicago", "Charleston", "Elmhurst", "University Park", "Chicago", "Lisle", "Normal", "Elgin", "Romeoville", "Chicago", "Lebanon", "Chicago", "Naperville", "Chicago", "Dekalb", "Evanston", "Chicago", "Bourbonnais", "Chicago", "Rockford", "Chicago", "River Forest", "Joliet", "Chicago", "Carbondale", "Edwardsville", "Macomb", "Anderson", "Mishawaka", "Indianapolis", "Winona Lake", "Indianapolis", "Evansville", "Terre Haute", "Richmond", "Marion", "Fort Wayne", "Valparaiso", "Dubuque", "Ames", "Iowa City", "Cedar Rapids", "Davenport", "Fayette", "Baldwin City", "Emporia", "Hays", "Wichita", "Lawrence", "Wichita", "Manhattan", "Olathe", "Pittsburg", "Leavenworth", "Winfield", "Topeka", "Wichita", "Louisville", "Campbellsville", "Williamsburg", "Midway", "Bowling Green", "Baton Rouge", "Ruston", "Lake Charles", "New Orleans", "Thibodaux", "Monroe", "Hammond", "Baton Rouge", "Lafayette", "New Orleans", "Orono", "Standish", "Portland", "Waterville", "Baltimore", "Bowie", "Frostburg", "Frederick", "Baltimore", "Baltimore", "Adelphi", "College Park", "Baltimore", "Emmitsburg", "Salisbury", "Springfield", "Paxton", "Worcester", "Longmeadow", "Waltham", "Chestnut Hill", "Boston", "Waltham", "Bridgewater", "Boston", "Worcester", "Milton", "Fitchburg", "Lowell", "Amherst", "Boston", "Boston", "Salem", "Boston", "Springfield", "North Dartmouth", "Boston", "Springfield", "Worcester", "Worcester", "Berrien Springs", "Mount Pleasant", "Grand Rapids", "Detroit", "Ypsilanti", "Flint", "Grand Rapids", "Southfield", "Ann Arbor", "East Lansing", "Dearborn", "Flint", "Rochester Hills", "University Center", "Adrian", "Spring Arbor", "Detroit", "Kalamazoo", "Minneapolis", "Saint Paul", "Saint Paul", "Saint Paul", "Saint Paul", "Minneapolis", "Saint Paul", "Saint Cloud", "Winona", "Saint Paul", "Saint Paul", "Marshall", "Winona", "Alcorn State", "Jackson", "Cleveland", "Jackson", "University", "Itta Bena", "Clinton", "Mississippi State", "Hattiesburg", "Hattiesburg", "Kansas City", "Warrensburg", "Springfield", "Springfield", "Saint Louis", "Saint Charles", "Saint Louis", "Maryville", "Parkville", "Kansas City", "Saint Louis", "Cape Girardeau", "Springfield", "Saint Louis", "Saint Louis", "Fulton", "Missoula", "Bellevue", "Chadron", "Omaha", "Lincoln", "Omaha", "Wayne", "Las Vegas", "Reno", "Rindge", "Henniker", "Manchester", "Plymouth", "Nashua", "Caldwell", "Hackettstown", "Teaneck", "Lodi", "Lakewood", "Glassboro", "Jersey City", "Union", "West Long Branch", "Montclair", "Newark", "Mahwah", "Lawrenceville", "New Brunswick", "Jersey City", "Hoboken", "Galloway", "Trenton", "Wayne", "Portales", "Las Vegas", "Albuquerque", "Las Cruces", "Hobbs", "Silver City", "Garden City", "Alfred", "Buffalo", "Potsdam", "New York", "New York", "Ithaca", "New York", "Brooklyn", "Bronx", "Buffalo", "Orangeburg", "Bronx", "Hempstead", "New Rochelle", "Keuka Park", "Syracuse", "Brookville", "Riverdale", "Poughkeepsie", "Dobbs Ferry", "Rockville Centre", "Newburgh", "Bronx", "New York", "New York", "Old Westbury", "New York", "New York", "Rochester", "Rochester", "Troy", "Saint Bonaventure", "Albany", "Brooklyn", "Rochester", "Queens", "Albany", "Vestal", "Buffalo", "Stony Brook", "Buffalo", "New Paltz", "Oswego", "Saratoga Springs", "Throggs Neck", "Syracuse", "New York", "Utica", "Staten Island", "Boone", "Buies Creek", "Greenville", "Elon", "Fayetteville", "Boiling Springs", "Hickory", "Montreat", "Greensboro", "Chapel Hill", "Charlotte", "Greensboro", "Durham", "Raleigh", "Wilmington", "Pembroke", "Misenheimer", "Charlotte", "Winston-Salem", "Wingate", "Cullowhee", "Bismarck", "Minot", "Grand Forks", "Fargo", "Akron", "Ashland", "Berea", "Bowling Green", "Columbus", "Cleveland", "Cincinnati", "Cleveland", "Dayton", "Findlay", "University Heights", "Kent", "Painesville", "Sylvania", "Canton", "Oxford", "Mount Vernon", "Cincinnati", "Columbus", "Columbus", "Athens", "Tiffin", "Toledo", "Cincinnati", "Pepper Pike", "North Canton", "Dayton", "Cincinnati", "Youngstown", "Bartlesville", "Bethany", "Edmond", "Tahlequah", "Stillwater", "Oklahoma City", "Norman", "Durant", "Weatherford", "Tulsa", "La Grande", "Newberg", "Eugene", "Corvallis", "Eugene", "Forest Grove", "Portland", "Portland", "Ashland", "Center Valley", "Reading", "Bloomsburg", "Radnor", "California", "Pittsburgh", "Pittsburgh", "Clarion", "Doylestown", "Philadelphia", "Pittsburgh", "Saint Davids", "Erie", "Beaver Falls", "Gwynedd Valley", "Philadelphia", "Indiana", "Philadelphia", "Annville", "Bethlehem", "Lincoln University", "Scranton", "Aston", "University Park", "Philadelphia", "Pittsburgh", "Rosemont", "Loretto", "Scranton", "Greensburg", "Shippensburg", "Slippery Rock", "Philadelphia", "Villanova", "Waynesburg", "West Chester", "Chester", "Wilkes-Barre", "York", "Smithfield", "Providence", "Providence", "Kingston", "Newport", "Anderson", "Charleston", "Central", "Charleston", "Clemson", "Tigerville", "Columbia", "Conway", "Rock Hill", "Sioux Falls", "Vermillion", "Clarksville", "Nashville", "Jefferson City", "Memphis", "Lebanon", "Nashville", "Johnson City", "Bristol", "Cleveland", "Harrogate", "Memphis", "Murfreesboro", "Chattanooga", "Knoxville", "Martin", "Nashville", "Cookeville", "Greeneville", "Jackson", "Abilene", "San Angelo", "Waco", "Austin", "Corpus Christi", "Dallas", "Irving", "Texarkana", "Commerce", "Houston", "Houston", "Houston", "Victoria", "Houston", "San Antonio", "Beaumont", "Laredo", "Longview", "Belton", "Wichita Falls", "Denton", "San Antonio", "Prairie View", "Houston", "Austin", "Houston", "Huntsville", "San Antonio", "Dallas", "Waxahachie", "Nacogdoches", "San Marcos", "Stephenville", "Kingsville", "College Station", "Arlington", "Austin", "Richardson", "El Paso", "Tyler", "Fort Worth", "San Antonio", "Houston", "Lubbock", "Denton", "Plainview", "Canyon", "Provo", "Cedar City", "Logan", "Orem", "Salt Lake City", "Ogden", "Salt Lake City", "Burlington", "Northfield", "Burlington", "Williamsburg", "Virginia Beach", "Harrisonburg", "Fairfax", "Hampton", "Harrisonburg", "Lynchburg", "Lynchburg", "Fredericksburg", "Arlington", "Norfolk", "Winchester", "Blacksburg", "Richmond", "Charlottesville", "Seattle", "Cheney", "Spokane", "Kirkland", "Tacoma", "Lacey", "Seattle", "Pullman", "Seattle", "Bellingham", "Spokane", "Fairmont", "Morgantown", "Milwaukee", "Milwaukee", "Waukesha", "Mequon", "Madison", "Plymouth", "Fond Du Lac", "Milwaukee", "La Crosse", "Eau Claire", "Oshkosh", "Milwaukee", "Platteville", "River Falls", "Laramie", "San Juan", "Carolina", "Gurabo", "West Lafayette", "Oklahoma City", "Irvine", "San Marcos", "Naples", "Seaside", "Salt Lake City", "Fort Myers", "Camarillo", "Los Alamitos", "Augusta"
#> $ locale <dbl+lbl> 12, 12, 12, 12, 12, 13, 12, 21, 13, 21, 33, 23, 11, 12, 11, 13, 12, 13, 13, 33, 13, 32, 32, 33, 21, 11, 12, 23, 11, 23, 12, 21, 13, 13, 11, 21, 21, 11, 11, 11, 11, 23, 11, 11, 11, 11, 12, 11, 13, 11, 11, 11, 33, 21, 11, 11, 11, 21, 21, 11, 21, 11, 13, 11, 11, 11, 11, 11, 12, 21, 21, 11, 11, 33, 11, 11, 12, 12, 12, 11, 11, 12, 12, 21, 21, 21, 12, 21, 21, 21, 21, 12, 13, 21, 21, 11, 11, 11, 11, 21, 13, 21, 13, 12, 13, 13, 21, 12, 12, 11, 12, 13, 11, 21, 12, 21, 23, 11, 21, 13, 12, 11, 13, 13, 13, 21, 12, 11, 11, 32, 32, 32, 12, 32, 13, 31, 11, 11, 11, 12, 13, 32, 22, 21, 12, 21, 11, 32, 21, 41, 11, 21, 22, 12, 21, 11, 21, 11, 12, 11, 23, 13, 11, 23, 11, 12, 11, 21, 21, 11, 13, 21, 33, 13, 13, 11, 32, 11, 22, 13, 41, 32, 11, 21, 13, 13, 13, 12, 12, 43, 31, 33, 33, 11, 13, 11, 13, 21, 32, 31, 32, 12, 11, 11, 32, 33, 42, 13, 12, 32, 13, 11, 13, 13, 13, 12, 12, 11, 23, 41, 13, 41, 11, 21, 23, 13, 11, 11, 21, 21, 11, 31, 23, 12, 41, 12, 21, 13, 13, 11, 13, 21, 11, 12, 21, 22, 21, 21, 11, 11, 21, 11, 12, 22, 11, 12, 12, 12, 31, 32, 21, 11, 21, 13, 12, 13, 12, 13, 13, 13, 21, 22, 32, 23, 11, 13, 11, 21, 11, 11, 11, 11, 21, 13, 32, 11, 11, 33, 32, 43, 12, 33, 12, 33, 33, 21, 33, 13, 13, 11, 32, 12, 12, 21, 13, 21, 33, 21, 11, 11, 13, 12, 21, 21, 32, 13, 21, 33, 11, 11, 11, 32, 12, 11, 41, 42, 22, 33, 13, 21, 21, 21, 21, 13, 21, 11, 21, 21, 21, 11, 21, 21, 13, 11, 21, 22, 13, 21, 33, 33, 11, 22, 41, 33, 21, 33, 11, 33, 11, 11, 13, 11, 11, 11, 11, 21, 11, 21, 21, 32, 21, 21, 11, 21, 21, 21, 13, 11, 11, 11, 21, 11, 11, 21, 21, 13, 33, 13, 11, 21, 11, 13, 22, 21, 21, 11, 21, 32, 23, 11, 12, 11, 13, 11, 32, 31, 13, 22, 12, 32, 13, 21, 11, 13, 11, 11, 11, 11, 12, 32, 42, 11, 12, 21, 32, 41, 33, 13, 12, 12, 31, 21, 31, 21, 11, 11, 11, 12, 32, 21, 21, 21, 21, 13, 31, 32, 21, 11, 11, 32, 32, 11, 11, 21, 21, 21, 11, 13, 32, 21, 21, 33, 32, 11, 22, 32, 33, 11, 33, 31, 12, 13, 12, 21, 11, 11, 22, 41, 13, 13, 21, 23, 11, 11, 33, 21, 11, 11, 21, 13, 21, 21, 11, 32, 11, 23, 13, 21, 13, 21, 13, 11, 11, 21, 31, 13, 21, 31, 32, 11, 21, 32, 21, 21, 13, 22, 21, 12, 12, 21, 21, 13, 12, 21, 12, 21, 41, 12, 13, 13, 12, 32, 12, 11, 23, 11, 31, 11, 13, 13, 13, 32, 11, 12, 12, 12, 33, 11, 33, 32, 13, 12, 12, 12, 11, 11, 11, 12, 41, 32, 11, 21, 11, 13, 11, 11, 12, 11, 13, 23, 12, 12, 11, 32, 11, 11, 11, 32, 11, 21, 21, 33, 13, 33, 32, 12, 11, 11, 12, 11, 12, 11, 11, 11, 11, 12, 33, 31, 12, 33, 13, 13, 12, 13, 12, 13, 32, 13, 23, 11, 13, 21, 12, 13, 13, 13, 22, 12, 12, 13, 13, 12, 23, 11, 31, 12, 21, 21, 13, 11, 32, 11, 13, 21, 32, 13, 11, 21, 13, 21, 11, 41, 13, 11, 13, 13, 13, 11, 32, 32, 33, 11, 21, 21, 13, 11, 11, 21, 21, 22, 21, 21, 22, 21, 12
#> $ urban <dbl+lbl> 2, 2, 2, 2, 2, 2, 2, 3, 2, 3, 4, 3, 1, 2, 1, 2, 2, 2, 2, 4, 2, 4, 4, 4, 3, 1, 2, 3, 1, 3, 2, 3, 2, 2, 1, 3, 3, 1, 1, 1, 1, 3, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 4, 3, 1, 1, 1, 3, 3, 1, 3, 1, 2, 1, 1, 1, 1, 1, 2, 3, 3, 1, 1, 4, 1, 1, 2, 2, 2, 1, 1, 2, 2, 3, 3, 3, 2, 3, 3, 3, 3, 2, 2, 3, 3, 1, 1, 1, 1, 3, 2, 3, 2, 2, 2, 2, 3, 2, 2, 1, 2, 2, 1, 3, 2, 3, 3, 1, 3, 2, 2, 1, 2, 2, 2, 3, 2, 1, 1, 4, 4, 4, 2, 4, 2, 4, 1, 1, 1, 2, 2, 4, 3, 3, 2, 3, 1, 4, 3, 4, 1, 3, 3, 2, 3, 1, 3, 1, 2, 1, 3, 2, 1, 3, 1, 2, 1, 3, 3, 1, 2, 3, 4, 2, 2, 1, 4, 1, 3, 2, 4, 4, 1, 3, 2, 2, 2, 2, 2, 4, 4, 4, 4, 1, 2, 1, 2, 3, 4, 4, 4, 2, 1, 1, 4, 4, 4, 2, 2, 4, 2, 1, 2, 2, 2, 2, 2, 1, 3, 4, 2, 4, 1, 3, 3, 2, 1, 1, 3, 3, 1, 4, 3, 2, 4, 2, 3, 2, 2, 1, 2, 3, 1, 2, 3, 3, 3, 3, 1, 1, 3, 1, 2, 3, 1, 2, 2, 2, 4, 4, 3, 1, 3, 2, 2, 2, 2, 2, 2, 2, 3, 3, 4, 3, 1, 2, 1, 3, 1, 1, 1, 1, 3, 2, 4, 1, 1, 4, 4, 4, 2, 4, 2, 4, 4, 3, 4, 2, 2, 1, 4, 2, 2, 3, 2, 3, 4, 3, 1, 1, 2, 2, 3, 3, 4, 2, 3, 4, 1, 1, 1, 4, 2, 1, 4, 4, 3, 4, 2, 3, 3, 3, 3, 2, 3, 1, 3, 3, 3, 1, 3, 3, 2, 1, 3, 3, 2, 3, 4, 4, 1, 3, 4, 4, 3, 4, 1, 4, 1, 1, 2, 1, 1, 1, 1, 3, 1, 3, 3, 4, 3, 3, 1, 3, 3, 3, 2, 1, 1, 1, 3, 1, 1, 3, 3, 2, 4, 2, 1, 3, 1, 2, 3, 3, 3, 1, 3, 4, 3, 1, 2, 1, 2, 1, 4, 4, 2, 3, 2, 4, 2, 3, 1, 2, 1, 1, 1, 1, 2, 4, 4, 1, 2, 3, 4, 4, 4, 2, 2, 2, 4, 3, 4, 3, 1, 1, 1, 2, 4, 3, 3, 3, 3, 2, 4, 4, 3, 1, 1, 4, 4, 1, 1, 3, 3, 3, 1, 2, 4, 3, 3, 4, 4, 1, 3, 4, 4, 1, 4, 4, 2, 2, 2, 3, 1, 1, 3, 4, 2, 2, 3, 3, 1, 1, 4, 3, 1, 1, 3, 2, 3, 3, 1, 4, 1, 3, 2, 3, 2, 3, 2, 1, 1, 3, 4, 2, 3, 4, 4, 1, 3, 4, 3, 3, 2, 3, 3, 2, 2, 3, 3, 2, 2, 3, 2, 3, 4, 2, 2, 2, 2, 4, 2, 1, 3, 1, 4, 1, 2, 2, 2, 4, 1, 2, 2, 2, 4, 1, 4, 4, 2, 2, 2, 2, 1, 1, 1, 2, 4, 4, 1, 3, 1, 2, 1, 1, 2, 1, 2, 3, 2, 2, 1, 4, 1, 1, 1, 4, 1, 3, 3, 4, 2, 4, 4, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 4, 4, 2, 4, 2, 2, 2, 2, 2, 2, 4, 2, 3, 1, 2, 3, 2, 2, 2, 2, 3, 2, 2, 2, 2, 2, 3, 1, 4, 2, 3, 3, 2, 1, 4, 1, 2, 3, 4, 2, 1, 3, 2, 3, 1, 4, 2, 1, 2, 2, 2, 1, 4, 4, 4, 1, 3, 3, 2, 1, 1, 3, 3, 3, 3, 3, 3, 3, 2
#> $ cipdig2 <chr> "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52", "52"
#> $ cipcode <chr> "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", "5202", 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#> $ creddesc <chr> "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's 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Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "Master's Degree", "...
#> $ ipedscount1 <dbl> 30, 115, 23, 95, 152, 210, 31, 23, 116, 44, 134, 42, 13, 444, 212, 118, 62, 123, 58, 15, 45, 66, 127, 22, 22, 168, 83, 24, 47, 55, 139, 17, 30, 55, 78, 168, 158, 103, 36, 43, 164, 155, 251, 862, 73, 126, 101, 73, 36, 12, 106, 11, 22, 370, 36, 37, 336, 37, 9, 44, 589, 79, 520, 211, 127, 73, 103, 114, 151, 162, 64, 640, 66, 29, 273, 91, 139, 67, 312, 44, 345, 96, 109, 29, 253, 21, 120, 148, 266, 65, 7, 67, NA, 159, 79, 56, 20, 372, 28, 85, 245, 81, 43, 49, 243, 374, 597, 34, 724, 25, 130, 232, 113, 706, 65, 134, 764, 127, 119, 65, 48, 164, 86, 24, 105, 77, 25, 399, 308, 15, 21, 103, 245, 37, 32, 100, 33, 142, 80, 120, 56, 14, 33, 87, 24, 91, 158, 48, 63, 17, 213, 434, 43, 65, 213, 215, 90, 77, 35, 110, 215, 468, 20, 79, 170, 49, 143, 69, 48, 43, 56, 65, 42, 102, 24, 63, 32, 74, 36, 48, 9, NA, 101, 40, 143, 64, 271, 44, 104, 105, 192, 45, 53, 97, 119, 45, 39, 43, 30, 87, 45, 44, 80, 51, 8, 66, 32, 128, 131, 51, 28, 76, 42, 24, 60, 44, 78, 68, 25, 19, 26, 49, 146, 0, 75, 42, 117, 122, 1934, 493, 76, 73, 40, 32, 31, 90, 86, 72, 239, 568, 140, 14, 94, 102, 32, 40, 219, 382, 124, NA, 36, 60, 22, 162, 111, 50, 74, 17, 23, 430, 338, 52, 40, 70, 44, 51, 787, 264, 65, 59, 117, 34, 27, 90, 166, 96, 72, 33, 93, 113, 72, 523, 45, 47, 160, 348, 50, 83, 27, 23, 194, 82, 19, 83, 22, 23, 93, 61, 45, 47, 29, 28, 18, 53, 42, 74, 53, 172, 158, 120, 56, 319, 407, 2045, 92, 52, 345, 73, 103, 87, 18, 23, 82, 122, 27, 24, 1408, 80, 23, 19, 62, 263, 20, 33, 56, 28, 30, 61, 108, 83, 34, 56, NA, 13, 134, 48, 74, 73, 95, 75, 175, 79, 18, 14, 144, 27, 103, 81, 158, 1205, 666, 130, 129, 37, 15, 11, 299, 74, 41, 24, 51, 57, NA, 58, 194, 53, 27, 9, 38, 1062, 208, 33, 28, 29, 120, 46, 60, 46, 36, 69, 126, 102, 101, 217, 71, 23, 29, 113, 71, 82, 162, 22, 17, 25, 62, 70, 191, 30, 40, 56, 45, 25, 16, 742, 128, 55, 32, 225, 53, 24, 83, 132, 291, 49, 56, 118, 32, 43, 31, 103, 183, 70, 21, 75, 159, 179, 218, 88, 195, 55, 61, 79, 18, 62, 53, 85, 24, 93, 344, 284, 49, 96, 43, 11, 66, 155, 138, 50, 78, 130, 45, 53, 140, 41, 118, 30, 47, 36, 43, 61, 33, 99, 159, 14, 94, 44, 34, 123, 58, 21, 10, 74, 54, 20, 33, 26, 19, 184, 75, 47, 49, NA, 38, 176, 57, 32, 35, 12, 21, 50, 88, 545, 103, 35, 49, 110, 42, 105, 27, 228, 373, 79, 78, 48, 77, 17, 8, 255, 87, 94, 63, 42, 71, 39, 46, 158, 48, 176, 52, 59, 51, 97, 32, 18, 36, 47, 52, 117, 73, 172, 28, 42, 133, 102, 103, 233, 38, 46, 77, 38, 66, NA, 26, 198, 58, 258, 206, 168, 62, 437, 51, 82, 283, 155, 287, 387, 63, 45, 33, 28, 20, 127, 102, 63, 331, 121, 99, 91, 28, 150, 10, 15, 107, 111, 43, 295, 303, 658, 337, 94, 350, 143, 100, 80, 276, 365, 216, 233, 228, 29, 126, 0, 298, 57, 114, 203, 179, 16, 182, 61, 21, 139, 29, 39, 1498, 36, 28, 43, 40, 35, 96, 102, 424, 208, 30, 152, 28, 40, 48, 237, 288, 407, 21, 33, 19, 34, 15, 172, 15, 135, 32, 115, 34, 105, 59, 55, 79, 243, 115, 45, 42, 120, 44, 159, 336, 89, 432, 46, 36, 75, 2336, 40, 40, NA, 38
#> $ ipedscount2 <dbl> 27, 133, 23, 89, 185, 247, 74, 19, 182, 48, 126, 34, 28, 299, 214, 121, 66, 128, 42, 8, 65, 56, 99, 38, 38, 235, 91, 38, 33, 69, 134, 24, 34, 58, 69, 99, 168, 131, 43, 49, 114, 172, 231, 808, 94, 120, 117, 59, 25, 11, 80, 13, 29, 393, 20, 29, 282, 54, 17, 32, 608, 85, 426, 169, 132, 81, 132, 118, 131, 151, 62, 670, 74, 29, 290, 88, 152, 92, 307, 55, 297, 88, 108, 27, 277, 38, 101, 130, 267, 82, 17, 59, NA, 140, 631, 117, 16, 381, 20, 130, 240, 67, 41, 58, 274, 386, 620, 33, 715, 37, 138, 239, 110, 686, 39, 182, 771, 148, 126, 46, 76, 139, 126, 27, 68, 83, 26, 421, 347, 29, 37, 118, 255, 23, 40, 101, 64, 127, 58, 145, 60, 9, 35, 106, 36, 169, 192, 55, 70, 29, 195, 345, 54, 37, 211, 207, 78, 23, 25, 79, 243, 481, 27, 67, 177, 38, 123, 52, 56, 28, 71, 67, 38, 109, 45, 46, 48, 83, 144, 70, 6, NA, 78, 27, 139, 67, 321, 51, 70, 123, 142, 37, 50, 89, 179, 41, 43, 69, 37, 113, 34, 23, 48, 48, 16, 106, 45, 180, 147, 47, 26, 53, 27, 36, 60, 48, 46, 64, 28, 15, 39, 57, 132, 0, 70, 32, 137, 141, 2309, 499, 46, 67, 36, 28, 20, 70, 93, 131, 248, 598, 87, 17, 66, 96, 29, 61, 257, 418, 132, NA, 23, 31, 17, 135, 119, 54, 54, 34, 18, 394, 296, 52, 45, 54, 46, 51, 763, 304, 56, 68, 99, 36, 24, 87, 261, 98, 145, 49, 160, 123, 65, 492, 45, 32, 229, 263, 52, 94, 25, 27, 281, 77, 33, 88, 22, 25, 96, 54, 21, 55, 32, 29, 14, 61, 80, 56, 46, 187, 185, 98, 43, 287, 367, 1790, 73, 68, 294, 74, 95, 120, 16, 20, 80, 129, 27, 50, 2074, 41, 30, 0, 81, 228, 13, 27, 71, 51, 24, 99, 140, 66, 30, 80, NA, 17, 123, 57, 86, 95, 74, 84, 193, 54, 23, 22, 158, 29, 100, 79, 133, 1216, 684, 163, 151, 34, 6, 12, 258, 72, 45, 35, 59, 135, NA, 48, 222, 47, 34, 17, 48, 1078, 274, 26, 40, 41, 134, 42, 55, 55, 29, 88, 138, 137, 118, 189, 48, 25, 27, 75, 117, 75, 344, 25, 44, 18, 55, 58, 209, 39, 60, 50, 54, 28, 25, 793, 98, 50, 23, 261, 74, 27, 61, 77, 270, 31, 63, 135, 42, 27, 24, 64, 225, 94, 21, 62, 156, 197, 225, 72, 158, 63, 71, 57, 21, 60, 50, 70, 42, 67, 308, 361, 56, 86, 42, 9, 39, 163, 139, 61, 44, 117, 27, 22, 144, 113, 134, 55, 34, 37, 43, 85, 34, 82, 214, 11, 108, 57, 30, 128, 58, 26, 20, 75, 58, 23, 39, 42, 26, 153, 66, 40, 24, 35, 54, 188, 45, 37, 54, 18, 14, 34, 116, 549, 126, 41, 29, 124, 31, 104, 14, 358, 265, 57, 132, 57, 49, 8, 24, 266, 97, 90, 74, 58, 79, 26, 42, 188, 39, 182, 46, 77, 92, 69, 30, 17, 56, 32, 48, 137, 55, 103, 32, 58, 119, 78, 121, 224, 35, 38, 88, 37, 44, 24, 62, 202, 92, 240, 82, 154, 52, 375, 32, 82, 434, 175, 255, 405, 68, 67, 27, 28, 18, 143, 76, 69, 315, 95, 107, 79, 34, 185, 24, 16, 87, 109, 45, 302, 390, 645, 373, 99, 393, 129, 119, 58, 239, 356, 207, 279, 223, 38, 138, 18, 305, 88, 102, 259, 171, 23, 302, 103, 16, 137, 29, 38, 1468, 29, 44, 52, 47, 47, 135, 98, 463, 134, 48, 159, 33, 28, 32, 212, 289, 401, 55, 28, 13, 42, 23, 140, 37, 229, 28, 119, 33, 126, 50, 73, 86, 217, 119, 31, 62, 114, 49, 170, 307, 68, 374, 60, 19, 79, 3209, 34, 39, NA, 31
#> $ debt_all_stgp_eval_n <dbl> 43, 70, 17, 39, 103, 139, 61, 14, 105, 10, 77, 22, 14, 409, 172, 123, 43, 97, 25, 11, 28, 39, 121, 16, NA, 110, 11, 16, 24, 65, 110, 10, 19, 38, 83, 71, 87, 99, 33, 40, 119, 123, 222, 509, 27, 59, 67, 48, 25, 15, 38, 14, 26, 116, 32, 57, 241, 41, 12, 11, 330, 77, 402, 73, 69, 46, 78, 34, 73, 120, 32, 464, 62, 25, 232, 73, 102, 64, 137, 26, 226, 57, 60, 17, 96, 13, 40, 17, 200, 30, 11, 74, NA, 69, 29, 121, 16, 226, 44, 60, 203, 64, 270, 56, 285, 146, 728, 38, 619, 18, 204, 170, 81, 874, 15, 130, 903, 186, 94, 27, 35, 80, 50, 41, 118, 85, 22, 160, 288, 26, 22, 86, 146, 26, 24, 97, 26, 49, 20, 106, 37, 15, 36, 105, 16, 112, 308, 24, 46, 20, 78, 435, 20, 22, 46, 128, 65, 48, 18, 57, 146, 121, 12, 70, 225, 15, 119, 63, 44, 33, 31, 33, 25, 116, 39, 14, 34, 53, 54, 43, 11, 475, 94, 30, 101, 50, 50, 32, 55, 86, 123, 21, 27, 111, 74, 15, 23, 56, 17, 73, 31, 16, 32, 12, 15, 48, 48, 70, 35, 25, 12, 68, 14, 12, 50, 64, 24, 31, 17, 12, 29, 39, 101, NA, 45, 16, 56, 67, 1463, 302, 40, 38, 22, 36, 17, 55, 43, 49, 124, 285, 56, 12, 32, 29, 31, 30, 79, 131, 65, 113, 10, 45, 40, 41, 82, 20, 21, 10, 14, 227, 369, 33, 42, 26, 19, 23, 527, 222, 27, 38, 44, 12, 32, 23, 130, 45, 101, 35, 203, 104, 61, 363, 26, 23, 180, 203, 42, 14, 12, 27, 285, 21, 30, 17, 14, 24, 48, 23, 15, 42, 18, 18, 18, 52, 36, 71, 31, 150, 103, 56, 26, 30, 231, 1030, 75, 44, 284, 47, 44, 40, 20, 11, 65, 64, 25, 11, 1836, 36, 11, 15, 47, 184, 11, 33, 46, 31, 18, 62, 122, 55, 15, 33, 354, 14, 23, 38, 34, 33, 55, 65, 113, 45, 27, 17, 62, 32, 77, 57, 59, 679, 432, 110, 79, 35, 10, 13, 201, 47, 18, 32, 41, 104, NA, 31, 283, 46, 36, 10, 39, 698, 23, 25, 22, 35, 76, 42, 52, 53, 58, 79, 73, 74, 81, 133, 30, 20, 13, 80, 30, 64, 227, 16, 28, 11, 53, 47, 93, 36, 13, 53, 39, 24, 34, 615, 73, 34, 31, 157, 44, 29, 83, 102, 284, 21, 48, 49, 28, 13, 11, 39, 83, 65, 25, 43, 97, 79, 187, 32, 80, 32, 41, 46, 17, 67, 34, 34, 36, 41, 172, 338, 19, 28, 52, 11, 65, 114, 93, 47, 73, 188, 21, 19, 38, 26, 62, 26, 21, 15, 42, 83, 26, 40, 93, 16, 85, 32, 18, 39, 70, 26, 15, 96, 60, 12, 30, 18, 12, 114, 66, 20, 43, NA, 33, 51, 29, 13, 10, 25, 13, 44, 264, 192, 98, 37, 21, 80, 39, 81, 21, 268, 217, 43, 20, 28, 41, 10, 13, 338, 32, 38, 41, 55, 84, 33, 44, 131, 24, 136, 50, 55, 43, 55, 18, 15, 25, 27, 43, 121, 43, 166, 28, 13, 69, 77, 102, 102, 33, 38, 46, 40, 29, 13, 31, 175, 85, 113, 126, 146, 50, 328, 41, 53, 430, 133, 189, 297, 34, 36, 39, 25, 13, 79, 109, 89, 159, 120, 46, 63, 15, 99, 16, 11, 68, 96, 34, 206, 112, 515, 260, 89, 363, 88, 114, 73, 224, 317, 49, 39, 174, 23, 126, 12, 331, 29, 97, 99, 131, 23, 273, 85, 11, 126, 17, 15, 1422, 12, 14, 42, 29, 29, 107, 80, 130, 95, 37, 145, 23, 35, 26, 93, 173, 319, 32, 24, 15, 36, 22, 133, 14, 79, 20, 104, 28, 66, 52, 47, 26, 205, 73, 20, 31, 190, 77, 194, 139, 63, 120, 46, 28, 97, 2793, 15, 37, NA, 17
#> $ debt_all_stgp_eval_mean <dbl> 52786, 34809, 57391, 23490, 33702, 45043, 25746, 23741, 34435, 36208, 35222, 18609, 32751, 53331, 46475, 37774, 39396, 36890, 33280, 27041, 18850, 50917, 33947, 24395, 45105, 25055, 44637, 28459, 24194, 29764, 44983, 32450, 27309, 25364, 35740, 32847, 32289, 40489, 33635, 35518, 31341, 78722, 75797, 94907, 69106, 92329, 77683, 33909, 42056, 28494, 43593, 49884, 18474, 55271, 48004, 43432, 39166, 45746, 38245, 45086, 85488, 40573, 41659, 53791, 53606, 49740, 64014, 33097, 63320, 66197, 33413, 90863, 55190, 41696, 54107, 45864, 52606, 32775, 43079, 47627, 45702, 38925, 43672, 31072, 50394, 30353, 28170, 23286, 32094, 26086, 26219, 33155, 24887, 32145, 32454, 82305, 34523, 73706, 44196, 46170, 31836, 40832, 38774, 33781, 41299, 37229, 61948, 35219, 42288, 35796, 53568, 78441, 32532, 58397, 30191, 48737, 49500, 34506, 42128, 41970, 28529, 37387, 30974, 41615, 45059, 36864, 30022, 67654, 72904, 24888, 27313, 29145, 60313, 23945, 35938, 24516, 36818, 48243, 40165, 37046, 29206, 46580, 33792, 32889, 30407, 32987, 49858, 19189, 31184, 47748, 51612, 37560, 25983, 35058, 40212, 70801, 29099, 43536, 44064, 29802, 35565, 115085, 16352, 29532, 29769, 33538, 45919, 58676, 32370, 54106, 37186, 26607, 27378, 36660, 27910, 37614, 21798, 29759, 21150, 25933, 22667, 43581, 26771, 71324, 18044, 31717, 36016, 40108, 47005, 39826, 40447, 18969, 26622, 37559, 28375, 19449, 37964, 33223, 16158, 33456, 30106, 30300, 22733, 39674, 25646, 16495, 28062, 33261, 42167, 19390, 19161, 31462, 21920, 28040, 23919, 52835, 31409, 86004, 22514, 26949, 28120, 24223, 50206, 43302, 29451, 29447, 42303, 52451, 48683, 71997, 36372, 23299, 22413, 25905, 21519, 25897, 35295, 32001, 54629, 54938, 65071, 25152, 29275, 31584, 39962, 16356, 29783, 35909, 31521, 38243, 27982, 63481, 27333, 32099, 55207, 30851, 42877, 11534, 49477, 34620, 45588, 58395, 44508, 29613, 30226, 53963, 75835, 49492, 34958, 40484, 34826, 40699, 28953, 30867, 37314, 40331, 39848, 40789, 32907, 44973, 41362, 61641, 29747, 29565, 33201, 46539, 44147, 24935, 26959, 55318, 46665, 22669, 25431, 21836, 40450, 36810, 28308, 24687, 28327, 30220, 24508, 20174, 26806, 41010, 30288, 33408, 18760, 36312, 30871, 42197, 18464, 23271, 83004, 48541, 17022, 37627, 46041, 25245, 27993, 35220, 17646, 17483, 41433, 24577, 24658, 33552, 41764, 43370, 21463, 30603, 35516, 32413, 33066, 26841, 29738, 34036, 38519, 26480, 38773, 52577, 39986, 37756, 58003, 37905, 37490, 27611, 27858, 32282, 30592, 27982, 32262, 25228, 33775, 35911, 37825, 31189, 35251, 38878, 45583, 96404, 103940, 41180, 21140, 25494, 35206, 36967, 61366, 68684, 36160, 29684, 24488, 62378, 31142, 32158, 39417, 30826, 30448, 64540, 65931, 108756, 50291, 28032, 57033, 39780, 46166, 35910, 20740, 31115, 33376, 38691, 39279, 31091, 24906, 39714, 50457, 30777, 22549, 26815, 49652, 38874, 72043, 36839, 26327, 43400, 24066, 29088, 30560, 53096, 31770, 34639, 34416, 40033, 37718, 82256, 35172, 29126, 72096, 39131, 34506, 32838, 31445, 47404, 58952, 29195, 28638, 26845, 17049, 17792, 19643, 47648, 30553, 35432, 40630, 37093, 67417, 36609, 36710, 19834, 30131, 27525, 45112, 30257, 37933, 25934, 30825, 29624, 27384, 34061, 54667, 38101, 27889, 45084, 29725, 30993, 34975, 40584, 35144, 27664, 31741, 32434, 36115, 25023, 23724, 41289, 43076, 21864, 27464, 17326, 28483, 38628, 30467, 46301, 70112, 48357, 43448, 41931, 30620, 38096, 31265, 23027, 24826, 29559, 36562, 43186, 32164, 29922, 39198, 44934, 37548, 33003, 30400, 30482, 33840, 27606, 40893, 20648, 39964, 32382, 41948, 31087, 41759, 75053, 36322, 33409, 35952, 40743, 38313, 24394, 22725, 59699, 42594, 21986, 23543, 43508, 35725, 30131, 28761, 26780, 23146, 32884, 18177, 32904, 37679, 28439, 39577, 38175, 23277, 42920, 23958, 32480, 23774, 25994, 29779, 40278, 24717, 31936, 24026, 42679, 27956, 36097, 25231, 46243, 37355, 29851, 31972, 42392, 31782, 32137, 18227, 19862, 40209, 38262, 21266, 61912, 37470, 15825, 51231, 53082, 17257, 30727, 38897, 33687, 36036, 37176, 40793, 38107, 25813, 19386, 42643, 28292, 26507, 25568, 40349, 41495, 37571, 46381, 42706, 32291, 29374, 98533, 33095, 24289, 23171, 31691, 18003, 42279, 34786, 76933, 43771, 33542, 32722, 48179, 33228, 55101, 36602, 30959, 39901, 32213, 34769, 17187, 29524, 27924, 47357, 28833, 46724, 23823, 41805, 41646, 53205, 46077, 17807, 45767, 28066, 33612, 35797, 20011, 38678, 60317, 34468, 34692, 42354, 48268, 93771, 45479, 29541, 39559, 37081, 40758, 42205, 48903, 40953, 56548, 30873, 32321, 28296, 27806, 28736, 34497, 23523, 31949, 39286, 36781, 33436, 48567, 31157, 36686, 34211, 31152, 31396, 24716, 34723, 38253, 28452, 30343, 48169, 39162, 50094, 37850, 38400, 40744, 14716, 18275, 33804, 24491, 33735
#> $ debt_all_stgp_eval_mdn <dbl> 50311, 30624, NA, 20004, 35889, 41000, 27500, NA, 34250, NA, 30750, 15400, NA, 44700, 41000, 29753, 40557, 38677, 33286, NA, 20500, 34760, 29743, NA, 46431, 23917, NA, NA, 23414, 31035, 43700, NA, 27500, 20500, 39656, 30728, 34166, 41000, 38662, 31756, 30750, 81000, 72389, 86864, 52347, 94019, 78548, 32699, 41000, NA, 41000, NA, 20500, 51548, 43380, 40500, 40394, 46750, NA, NA, 91630, 41000, 41000, 53604, 47808, 49626, 49450, 31500, 63550, 59380, 41000, 79041, 51250, 43252, 52152, 39681, 51807, 32518, 42500, 44866, 41000, 39934, 41000, NA, 41000, NA, 20500, NA, 30393, 20500, NA, 34572, NA, 30750, 32500, 85000, NA, 65500, 45001, 41000, 29871, 39801, 34560, 33750, 41000, 32000, 61469, 36958, 38524, NA, 53024, 77865, 30750, 51250, NA, 41000, 54454, 31158, 27142, 39448, 30048, 40678, 28646, 40308, 41000, 41000, 30842, 61500, 79888, 20206, 22000, 29000, 58726, 20833, 32950, 20500, 35398, 45836, 41000, 40529, 23451, NA, 36149, 32825, NA, 30509, 48500, 18178, 31025, 51250, 49500, 34580, 25200, 40100, 35778, 61500, 29015, 41000, NA, 29700, 32046, 106803, NA, 33900, 28500, NA, 42300, 50607, 31626, 50718, 40516, 19485, 20794, 36960, 29303, NA, 24458, 30893, 18516, 26739, NA, 45581, 25028, 50048, 14500, 29964, 40268, 39964, 45641, 46322, 43770, 19706, 23774, 40916, 28930, NA, 31727, 35933, NA, 38525, 30050, NA, 21000, NA, NA, 13098, 25991, 30750, 41000, 18007, NA, 34750, NA, NA, 21054, 51250, 30750, 98616, NA, NA, 20298, 20500, 41000, NA, 20800, NA, 39000, 50339, 46000, 68411, 39210, 20945, 23014, 22926, NA, 24163, 36979, 27502, 46711, 49318, 65000, NA, 27255, 20500, 41000, 17307, 27257, 32926, 30750, 37380, NA, 61500, 26262, 20500, 50646, 27333, 41000, NA, NA, 34689, 34000, 36722, 40007, 32280, 36805, 57796, 51250, 51250, 31596, 37294, 34100, NA, 30519, 27333, 38000, 36500, 37199, 41000, 36083, 41000, 38622, 60249, 34075, 27934, 33885, 43105, 44200, NA, NA, 41000, 47706, 23983, 20500, NA, NA, 31000, 20500, 25800, NA, 32197, NA, NA, NA, 41000, 28700, 32295, 18622, 34687, 27200, 40000, 17916, 20350, 77292, 46812, 16615, 31353, 41000, 26041, 28895, 33933, 17300, NA, 37106, 20500, 25570, NA, 40969, 41000, NA, NA, 40692, 30166, NA, 28072, 28750, 36500, NA, 20500, 40902, 50352, NA, 34750, 53414, NA, 34732, 21558, 27768, 32238, 30550, 27462, 29017, 22801, 34166, NA, 35750, 30500, 34167, 42729, 38500, 69500, 111446, 40977, 18580, 23174, NA, NA, 50451, 59132, NA, 33258, 20500, 65000, 31721, 26720, 35875, 30500, 27417, NA, 57930, 95353, 41000, 27750, 61500, 41000, 45268, 35826, 20500, 30500, 30500, 30290, 33672, 31874, 20500, 40000, 38523, 30750, NA, 22747, 51935, 34029, 70653, NA, 25000, NA, 20602, 24375, 25500, 49805, NA, 34839, 34240, 41000, 40316, 74873, 31486, 30574, 60065, 41000, 40445, 30761, 33698, 41814, 57519, 28910, 30193, 29029, 15780, NA, NA, 39806, 26252, 36659, 43491, 33705, 65000, 30750, 34962, 19092, 28518, 20500, 38605, 28607, NA, 25978, 33077, 32675, 24787, 30216, 47440, 41000, 30833, 41525, 30750, NA, 31333, 34133, 35004, 26584, 34166, 36163, 35500, 25356, 17197, 33069, 40460, 22851, 29473, NA, 31000, 41000, 29542, 37249, 70874, NA, 41000, 44312, NA, 41325, 29202, 23500, NA, 27533, 39220, NA, 30149, NA, NA, 42993, 41000, 36343, 32894, 35500, 35875, 26500, 29035, NA, NA, 33821, NA, 34123, 41000, 41000, 36114, 30000, 30750, 42553, 26500, 21195, 20500, 44750, 39907, 22705, 20500, 41000, 37289, NA, NA, 27735, 20500, 30750, 17490, 33848, 37848, 30871, 40808, 39057, 23756, 41000, 20500, 33322, 20500, 20992, NA, NA, 25414, 36527, 25546, 36614, 25281, 41000, 25525, NA, 29011, 26200, 30394, 38500, 29194, 28959, 12725, 17574, 30069, NA, 20500, 57000, 41000, 15199, 51250, 54678, 15488, 27956, 41000, 32302, 40370, 34724, 41000, 37584, 27582, 17800, 42173, 28577, NA, 21350, 41000, 41000, 30750, 43750, 41000, 34961, NA, 90123, NA, NA, 20359, 29604, 18000, 36453, 29203, 82067, 41200, 34418, 34166, 41000, 24666, 53184, 36979, 30552, 36995, 33245, 41000, 13850, 28000, NA, 41000, 30000, 44417, 20500, 39350, 44879, 47060, 41000, NA, 40899, NA, NA, 34166, NA, NA, 61500, 30750, 34936, 35682, 41000, 85690, 47559, 29892, 34644, 40999, 41208, 41000, 41000, 37500, 55437, 30200, 34167, NA, 22500, 29122, 37649, NA, 25319, 36832, 40940, 35500, 37474, 28840, 32650, 37824, 25823, 32720, 25194, 30731, 36007, 29172, 29917, 43811, 41000, 52120, 39940, 30000, 41470, 13319, NA, 30978, 22866, NA
#> $ debt_all_stgp_eval_mdn10yrpay <dbl> 517, 314, NA, 205, 368, 421, 282, NA, 352, NA, 316, 158, NA, 459, 421, 305, 416, 397, 342, NA, 210, 357, 305, NA, 477, 246, NA, NA, 240, 319, 449, NA, 282, 210, 407, 316, 351, 421, 397, 326, 316, 832, 743, 892, 537, 965, 807, 336, 421, NA, 421, NA, 210, 529, 445, 416, 415, 480, NA, NA, 941, 421, 421, 550, 491, 510, 508, 323, 653, 610, 421, 812, 526, 444, 535, 407, 532, 334, 436, 461, 421, 410, 421, NA, 421, NA, 210, NA, 312, 210, NA, 355, NA, 316, 334, 873, NA, 673, 462, 421, 307, 409, 355, 347, 421, 329, 631, 379, 396, NA, 544, 799, 316, 526, NA, 421, 559, 320, 279, 405, 309, 418, 294, 414, 421, 421, 317, 631, 820, 207, 226, 298, 603, 214, 338, 210, 363, 471, 421, 416, 241, NA, 371, 337, NA, 313, 498, 187, 319, 526, 508, 355, 259, 412, 367, 631, 298, 421, NA, 305, 329, 1097, NA, 348, 293, NA, 434, 520, 325, 521, 416, 200, 214, 379, 301, NA, 251, 317, 190, 275, NA, 468, 257, 514, 149, 308, 413, 410, 469, 476, 449, 202, 244, 420, 297, NA, 326, 369, NA, 396, 309, NA, 216, NA, NA, 134, 267, 316, 421, 185, NA, 357, NA, NA, 216, 526, 316, 1013, NA, NA, 208, 210, 421, NA, 214, NA, 400, 517, 472, 702, 403, 215, 236, 235, NA, 248, 380, 282, 480, 506, 667, NA, 280, 210, 421, 178, 280, 338, 316, 384, NA, 631, 270, 210, 520, 281, 421, NA, NA, 356, 349, 377, 411, 331, 378, 593, 526, 526, 324, 383, 350, NA, 313, 281, 390, 375, 382, 421, 370, 421, 397, 619, 350, 287, 348, 443, 454, NA, NA, 421, 490, 246, 210, NA, NA, 318, 210, 265, NA, 331, NA, NA, NA, 421, 295, 332, 191, 356, 279, 411, 184, 209, 794, 481, 171, 322, 421, 267, 297, 348, 178, NA, 381, 210, 263, NA, 421, 421, NA, NA, 418, 310, NA, 288, 295, 375, NA, 210, 420, 517, NA, 357, 548, NA, 357, 221, 285, 331, 314, 282, 298, 234, 351, NA, 367, 313, 351, 439, 395, 714, 1144, 421, 191, 238, NA, NA, 518, 607, NA, 341, 210, 667, 326, 274, 368, 313, 282, NA, 595, 979, 421, 285, 631, 421, 465, 368, 210, 313, 313, 311, 346, 327, 210, 411, 396, 316, NA, 234, 533, 349, 725, NA, 257, NA, 212, 250, 262, 511, NA, 358, 352, 421, 414, 769, 323, 314, 617, 421, 415, 316, 346, 429, 591, 297, 310, 298, 162, NA, NA, 409, 270, 376, 447, 346, 667, 316, 359, 196, 293, 210, 396, 294, NA, 267, 340, 335, 255, 310, 487, 421, 317, 426, 316, NA, 322, 350, 359, 273, 351, 371, 365, 260, 177, 340, 415, 235, 303, NA, 318, 421, 303, 382, 728, NA, 421, 455, NA, 424, 300, 241, NA, 283, 403, NA, 310, NA, NA, 441, 421, 373, 338, 365, 368, 272, 298, NA, NA, 347, NA, 350, 421, 421, 371, 308, 316, 437, 272, 218, 210, 459, 410, 233, 210, 421, 383, NA, NA, 285, 210, 316, 180, 348, 389, 317, 419, 401, 244, 421, 210, 342, 210, 216, NA, NA, 261, 375, 262, 376, 260, 421, 262, NA, 298, 269, 312, 395, 300, 297, 131, 180, 309, NA, 210, 585, 421, 156, 526, 561, 159, 287, 421, 332, 415, 357, 421, 386, 283, 183, 433, 293, NA, 219, 421, 421, 316, 449, 421, 359, NA, 925, NA, NA, 209, 304, 185, 374, 300, 843, 423, 353, 351, 421, 253, 546, 380, 314, 380, 341, 421, 142, 287, NA, 421, 308, 456, 210, 404, 461, 483, 421, NA, 420, NA, NA, 351, NA, NA, 631, 316, 359, 366, 421, 880, 488, 307, 356, 421, 423, 421, 421, 385, 569, 310, 351, NA, 231, 299, 387, NA, 260, 378, 420, 365, 385, 296, 335, 388, 265, 336, 259, 316, 370, 300, 307, 450, 421, 535, 410, 308, 426, 137, NA, 318, 235, NA
#> $ earn_count_wne_hi_1yr <dbl> 45, 87, NA, 57, 119, 177, 32, 12, 94, 15, 129, 22, 19, 608, 208, 161, 49, 91, 37, NA, 25, 58, 151, 32, 117, 73, 12, NA, 53, 52, 128, 18, 22, 44, 91, 86, 92, 85, 24, 37, 173, 76, 290, 733, 18, 78, 75, 52, 17, NA, 63, 15, 22, 260, 36, 58, 303, 38, NA, 25, 369, 68, 416, 81, 105, 55, 80, 71, 104, 172, 47, 501, 70, 28, 287, 68, 144, 62, 265, NA, 333, 83, 65, 23, 217, NA, 132, 17, 262, 62, 18, 78, 20, 111, 80, 76, 16, 307, 48, 76, 208, 75, 326, 48, 299, 277, 655, 41, 799, 14, 192, 211, 109, 824, 46, 157, 895, 287, 90, 46, 33, 90, 56, 47, 121, 94, 30, 197, 322, 16, 34, 104, 157, 52, 28, 135, 21, 78, 41, 118, 59, 17, 35, 115, 23, 84, 357, 50, 51, 25, 107, 403, 30, 13, 56, 138, 103, 82, 46, 71, 218, 118, 11, 86, 168, 26, 156, 89, 50, 43, 49, 56, 48, 133, 25, 19, 23, 62, 34, 38, 13, 631, 106, 27, 141, 70, 200, 52, 123, 69, 344, 25, 43, 138, 100, 47, 32, 59, 31, 72, 40, 24, 65, NA, NA, 52, 42, 67, 39, 34, 14, 108, 20, 21, 59, 46, 58, 41, 28, 21, 26, 50, 109, 12, 79, 24, 71, 125, 1575, 409, 48, 71, 39, 45, NA, 115, 33, 48, 201, 371, 91, 16, 40, 69, 28, 35, 139, 330, 89, 78, 24, 81, 47, 50, 89, 58, 56, NA, 22, 301, 374, 37, 48, 47, 56, 57, 648, 230, 63, 44, 92, 22, 39, NA, 151, 108, 78, 79, 188, 113, 56, 275, 21, 45, 156, 351, 41, 30, 17, 19, 240, 13, 23, 52, 15, 19, 71, 48, 30, 40, 43, 24, 25, 69, 74, 93, 51, 91, 130, 89, 37, 50, 273, 1521, 138, 41, 349, 63, 117, 80, 17, 24, 69, 109, 26, 16, 1841, 64, 15, 22, 80, 200, 24, 36, 58, 20, 29, 101, 122, 65, 38, 46, 410, 15, 30, 49, 57, 70, 70, 66, 155, 39, 18, 18, 103, 36, 100, 93, 108, 723, 474, 136, 66, 44, 17, 14, 274, 54, 26, 35, 81, 102, 32, 61, 225, 41, 34, NA, 43, 980, 22, 42, 28, 12, 88, 44, 87, 60, 65, 100, 93, 85, 102, 183, 60, 13, 32, 112, 55, 71, 163, 11, NA, 31, 58, 62, 117, 24, 20, 58, 39, 36, 19, 678, 93, 49, 28, 171, 39, 17, 100, 88, 340, 46, 52, 57, 22, 38, 25, 77, 158, 106, 36, 75, 127, 127, 222, 63, 84, 61, 62, 91, 33, 77, 46, 31, 24, 50, 267, 362, 17, 47, 49, 19, 77, 119, 113, 59, 77, 163, 48, 35, 67, 24, 82, 37, 30, 27, 21, 83, 29, 35, 149, 18, 84, 48, 28, 105, 81, 20, 14, 94, 58, 16, 40, 37, 25, 208, 44, 57, 51, 61, 36, 58, 75, 40, 24, NA, 21, 37, 405, 313, 153, 43, 30, 101, 61, 111, 28, 254, 221, 87, 55, 29, 69, 25, 18, 310, 82, 72, 71, 42, 101, 16, 37, 117, NA, 186, 72, 64, 39, 96, 23, 17, 24, 54, 39, 148, 60, 124, 35, 20, 118, 103, 116, 154, 33, 45, 72, 48, 71, NA, 28, 157, 66, 130, 139, 171, 45, 463, 68, 85, 215, 157, 255, 361, 25, 61, 41, 29, 18, 102, 122, 79, 229, 120, 53, 103, 17, 117, NA, 19, 112, 122, 92, 289, 175, 649, 323, 107, 378, 140, 122, 99, 251, 491, 39, NA, 259, 25, 172, NA, 311, 37, 120, 109, 107, 12, 247, 49, NA, 175, 16, 42, 1725, 20, 29, 37, 41, 23, 97, 112, 172, 125, 34, 192, 20, 43, 37, 151, 228, 475, 31, 29, 16, 29, 28, 187, 23, 81, 28, 144, 36, 130, 69, 68, 79, 269, 83, 38, 23, 154, 50, 174, 163, 78, 196, 59, 36, 97, 2462, 37, 50, 47, 29
#> $ earn_mdn_hi_1yr <dbl> 40737, 67202, NA, 68499, 81031, 107636, 45529, 53358, 66686, 65053, 60240, 58673, 82882, 98670, 97211, 63377, 67101, 127000, 59986, NA, 57318, 54948, 71255, 55286, 62756, 63005, 79450, NA, 68499, 66573, 73378, 82440, 61814, 63749, 84161, 76460, 78719, 74063, 101406, 95739, 74576, 108244, 103705, 150453, 55338, 109763, 78134, 63005, 71575, NA, 114223, 122038, 55512, 75573, 62260, 71435, 65310, 77401, NA, 67420, 99335, 64493, 74641, 79284, 92410, 76460, 98403, 98213, 133919, 109763, 74200, 128506, 69897, 37208, 89790, 67660, 81391, 59124, 94851, NA, 71575, 65984, 54109, 74576, 115897, NA, 91211, 52524, 69218, 76930, 60320, 63997, 69338, 92885, 58866, 89130, 48823, 112701, 63600, 54531, 45665, 50606, 75957, 53608, 67660, 76325, 69119, 61814, 89535, 81812, 41193, 76041, 69967, 56329, 58221, 66062, 56796, 69032, 50606, 65131, 51106, 60485, 55964, 40402, 58173, 52107, 54035, 130046, 127602, 57318, 64990, 73635, 105167, 41937, 53108, 60920, 64493, 75623, 64990, 76773, 62579, 90412, 71486, 67273, 72796, 58221, 101406, 53984, 73041, 76460, 81807, 72685, 70176, 91744, 61218, 84653, 60452, 68219, 71351, 62012, 93555, 160423, 63005, 53244, 54442, 74200, 60275, 52789, 74307, 62012, 57318, 70176, 66325, 69338, 48198, 97071, 54435, 74576, 61516, 69338, 43798, 66941, 63855, 68666, 64865, 79473, 97959, 71575, 82440, 72719, 69146, 63005, 55286, 58221, 82238, 67660, 66045, 54192, 46478, 65131, 55713, 69338, 71015, NA, NA, 50856, 47260, 52420, 60878, 60839, 53358, 60399, 54635, 78343, 50856, 44942, 52107, 104749, 55036, 74576, 60771, 50231, 79473, 70456, 73769, 69338, 105083, 93646, 74230, 108154, 56234, 65089, 55964, 41789, NA, 64940, 55108, 102409, 115060, 111713, 73949, 63005, 63005, 70112, 77401, 75921, 83270, 109492, 77401, 62632, 79450, 76083, 47260, 63005, 72902, 72605, 122038, NA, 52107, 66631, 62674, 64990, 61888, 109095, 65486, 91078, 140364, 100951, 97071, 71854, 90146, 55338, 57995, NA, 80004, 77297, 74576, 82882, 78971, 74262, 57318, 115006, 67362, 81333, 75352, 107198, 77715, 53629, 52107, 38289, 47025, 41007, 46478, 70009, 31670, 63005, 79598, 49136, 52941, 53472, 53608, 55964, 49621, 54585, 57318, 54739, 48901, 61888, 68666, 81491, 55964, 71392, 112939, 65476, 54621, 61516, 75405, 74576, 80082, 83768, 44170, 71575, 93816, 79884, 58673, 62012, 68321, 60771, 69338, 70456, 87309, 76729, 70009, 60298, 77087, 64196, 59124, 67660, 89613, 84653, 100690, 90264, 112363, 57318, 114225, 56931, 82440, 68666, 71854, 54296, 64196, 52941, 69338, 55964, 68047, 34420, 62756, 68422, 52492, 166356, 155273, 101494, 54534, 55211, 51273, 67660, 108092, 105863, 47260, 61020, 56276, 61651, 71015, 84653, 61859, 66449, 56641, NA, 54109, 150006, 63005, 59648, 109763, 57318, 66049, 55078, 54470, 54769, 66293, 58402, 63898, 71575, 68499, 76208, 60185, 52107, 56776, 59288, 72325, 75706, 93768, 48041, NA, 57318, 54109, 56931, 63275, 76460, 50856, 56234, 50856, 53775, 53358, 135907, 82440, 66728, 53775, 86997, 61814, 52107, 61859, 87309, 81491, 89968, 68079, 61516, 41349, 73949, 63005, 73231, 73500, 89841, 81997, 80234, 81836, 79284, 67918, 64150, 65238, 64493, 75518, 60623, 48823, 56641, 99960, 43426, 59350, 61303, 98720, 89083, 52107, 70596, 72762, 63005, 68079, 68708, 83848, 80166, 57860, 55456, 57770, 69338, 72274, 81333, 106421, 61177, 54035, 57995, 61516, 76460, 55964, 63005, 82808, 57318, 91539, 67995, 58221, 82756, 66287, 55964, 54713, 55964, 63997, 63005, 65332, 63749, 94408, 65238, 53045, 62579, 48432, 62012, 84653, 61020, 82756, 79284, 120549, NA, 47846, 59045, 95618, 179111, 57149, 61516, 50606, 91502, 55964, 67660, 54869, 110109, 108265, 75204, 87815, 59485, 55693, 66821, 78971, 51690, 65734, 82440, 61681, 58943, 63749, 51273, 57318, 72983, NA, 102902, 49883, 57017, 61064, 77144, 50856, 54713, 52941, 75330, 57995, 58402, 52107, 49527, 44021, 52107, 75282, 64493, 76460, 102743, 57318, 53984, 63997, 60523, 72860, NA, 55286, 100087, 69897, 68858, 62546, 73486, 48041, 75097, 71575, 82756, 66772, 70680, 99069, 62528, 53358, 46254, 58673, 61020, 60433, 86036, 58221, 64493, 128149, 74200, 65486, 73852, 72482, 111769, NA, 56415, 68548, 64150, 59576, 105083, 73164, 137496, 95317, 63005, 73787, 108532, 75204, 59350, 84653, 67524, 63005, NA, 121825, 64493, 83704, NA, 100554, 81491, 83915, 79284, 79150, 58673, 69165, 56234, NA, 102902, 67660, 105465, 60729, 69338, 74200, 87604, 63005, 62260, 121046, 93467, 173400, 81886, 46478, 85243, 57318, 64990, 57318, 91211, 98551, 135440, 62012, 63997, 35416, 62409, 61218, 69338, 66915, 73399, 73949, 65524, 63005, 100738, 57318, 84653, 83388, 64295, 79541, 77715, 73949, 35351, 32806, 37208, 96288, 54509, 71575, 72274, 51607, 77297, 71819, 71015, 83388, 63997, 65657
#> $ earn_count_wne_hi_2yr <dbl> 37, 74, NA, NA, 95, 131, 11, NA, 72, 12, 109, 16, 13, 552, 148, 172, 34, 54, 31, NA, 13, 50, 73, 27, 121, 32, NA, NA, 52, 62, 91, 19, 25, 33, 85, 72, 53, 58, 21, 36, 182, 108, 159, 654, 14, 70, 82, 37, NA, 14, 50, NA, NA, 272, 21, 35, 222, 48, NA, 13, 376, 24, 258, 37, 116, 49, 90, 35, 105, 134, 46, 638, 95, 12, 266, 69, 165, 43, 161, 32, 278, 80, 28, 22, 174, NA, 105, NA, 164, 41, 16, 52, NA, 35, 37, 73, 13, 370, 46, 99, 136, NA, 166, 36, 216, 247, 681, 34, 717, NA, 217, 185, 94, 590, 76, 128, 717, 223, 67, 54, 29, 30, 59, 34, 46, 66, 23, 170, 293, 16, NA, 87, 130, 51, 23, 83, 27, 81, 22, 100, 37, 14, 21, 78, 18, 76, 316, 34, 46, 29, 88, 150, 28, NA, 150, 94, 80, 66, 35, 90, 192, 116, NA, 55, 88, 23, 136, 79, 30, 43, 64, 43, 29, 131, 15, NA, NA, 42, 19, 20, NA, 504, 88, 22, 86, 42, 193, 40, 104, 30, 358, 15, 39, 82, 45, 44, 14, 38, 21, 41, 33, 13, 34, NA, NA, 18, 16, 48, 33, 16, 15, 120, 25, 19, 42, 52, 53, 53, 13, NA, 16, 55, 31, NA, 43, 21, 61, 133, 1384, 287, 47, 67, 26, 30, 23, 93, 34, 51, 189, 313, 52, 16, NA, 62, 31, 35, 68, 218, 69, 54, 14, 82, 17, 21, 71, 43, 43, 21, 16, 251, 246, 37, 30, 33, 59, 45, 626, 128, 54, 19, 70, 18, 27, NA, 134, 109, 58, 64, 142, 95, 52, 89, NA, 32, 144, 297, 31, 30, NA, NA, 220, 16, 21, NA, 14, 18, 47, 24, 17, 34, 42, 16, 31, 40, 44, 73, 41, 19, 104, 89, 19, 59, 122, 1114, 99, 47, 205, 54, 124, 79, 15, 12, 71, 93, 15, 17, 1017, 38, 15, 18, 104, 173, NA, 21, 36, 25, 20, 94, 53, 56, 29, 35, 201, NA, 28, 35, 56, 42, 46, 59, 108, NA, NA, 12, 62, 22, 73, 66, 76, 665, 466, 117, 19, 43, 13, NA, 249, 46, 22, 22, 63, 104, 19, 52, 143, 26, 35, NA, 51, 942, 17, 26, 24, NA, 50, 35, 72, 22, 49, 84, 81, 38, 73, 99, 47, 16, 23, 46, 37, 46, 45, NA, NA, 28, 43, 63, 110, 30, 19, 39, 19, 40, 14, 315, 70, 44, 20, 74, 23, 11, 54, 37, 289, 33, 58, 29, 13, 18, 21, 46, 115, 96, 56, 48, 116, 60, 250, 53, 52, 40, 60, 67, 35, 82, 31, 33, NA, 35, 224, 305, NA, 37, 26, 14, 58, 56, 78, 45, 23, 75, 48, 27, 27, 37, 57, 16, 13, 19, NA, 94, NA, 30, 99, NA, 82, 38, 19, 100, 72, NA, NA, 57, 21, 25, 45, 37, 25, 129, 21, 51, 17, 33, 38, 50, 43, 40, 17, NA, 14, 19, 376, 270, 176, 35, NA, 113, 46, 81, 28, 167, 89, 59, 37, 16, 59, 11, 13, 220, 63, NA, 75, 37, 74, 21, 13, 99, NA, 154, 46, 59, 28, 58, 14, 15, 19, 61, 25, 103, 23, 31, 18, 12, 118, 64, 84, 159, 18, 36, 46, 48, 50, NA, NA, 106, 43, 25, 129, 186, 31, 355, 35, 78, 38, 151, 265, 314, 21, 66, 29, 18, 15, 84, 82, 53, 194, 103, 21, 94, NA, 113, NA, 14, 87, 118, 130, 272, 165, 591, 210, 78, 185, 125, 90, 89, 170, 446, 37, NA, 199, 22, 100, NA, 113, 38, 112, 45, 111, NA, 201, 26, NA, 138, 32, 39, 1359, NA, 28, 27, 20, 16, 68, 116, 310, 91, 21, 178, 21, 23, 33, 140, 149, 476, 34, 16, NA, 19, 37, 193, 20, 81, 15, 143, 11, 128, 48, 63, 43, 226, 49, 32, 17, 158, 51, 137, 88, 51, 156, 46, 21, 93, 1704, 39, 35, 14, 23
#> $ earn_mdn_hi_2yr <dbl> 43798, 70176, NA, NA, 80004, 114892, 50856, NA, 66461, 52107, 58549, 58221, 81333, 98650, 92743, 65042, 54739, 106421, 57318, NA, 48432, 67101, 74105, 58402, 59425, 73075, NA, NA, 71015, 73949, 72214, 85357, 50856, 69338, 90049, 80779, 79838, 67660, 106421, 88907, 73739, 116258, 90983, 143744, 60320, 101406, 80459, 62012, NA, 63005, 88861, NA, NA, 69657, 47260, 67660, 65238, 78074, NA, 76460, 92733, 69338, 79037, 68499, 89672, 80124, 96866, 87973, 128588, 108331, 83768, 131090, 63997, 47260, 89184, 71015, 80503, 66541, 80301, 54661, 66897, 57318, 60161, 87604, 106249, NA, 90348, NA, 70044, 73949, 52941, 64706, NA, 86424, 54697, 99458, 41193, 114046, 61303, 51482, 46790, NA, 75047, 52107, 59688, 75787, 67685, 61020, 88546, NA, 39653, 83022, 65557, 58605, 60689, 62806, 56918, 66566, 53358, 62260, 45696, 59253, 49854, 38289, 60173, 53894, 51106, 134287, 127034, 52941, NA, 65486, 111283, 41342, 55964, 62343, 56415, 78719, 49683, 74786, 61516, 84653, 64493, 65238, 84653, 59576, 100096, 54386, 84653, 73635, 80189, 71661, 72884, NA, 60071, 87470, 59942, 63600, 62260, 58303, 91587, 189565, NA, 48432, 57770, 68778, 61350, 55840, 69338, 71957, 54809, 56931, 63166, 65238, 52107, NA, NA, 62260, 61020, 63005, NA, 66326, 64706, 63005, 57589, 70680, 96991, 68666, 78657, 63005, 67473, 67660, 55286, 57995, 73299, 57318, 56641, 61218, 48432, 69338, 60523, 71015, 57318, NA, NA, 49787, 48432, 61144, 36560, 84653, 61814, 63692, 56641, 67101, 51106, 49344, 46869, 87973, 58673, NA, 58673, 49883, 75204, NA, 78719, 74576, 106421, 92188, 72006, 106102, 51750, 68331, 53537, 52107, 52107, 64572, 63005, 89968, 115060, 106688, 72214, 61177, NA, 64328, 82882, 75518, 71854, 99741, 74200, 61516, 78971, 71778, 46478, 68666, 83388, 71015, 119061, 53775, 69338, 65180, 63318, 81111, 66077, 103746, 64493, 89968, 140166, 98481, 90856, 73635, 89412, 57318, 60771, NA, 90079, 73801, 72602, 80858, 75795, 65238, 65131, 112319, NA, 75204, 72469, 101300, 66915, 55964, NA, NA, 46673, 55964, 46087, NA, 33993, 59722, 88527, 53358, 50465, 59969, 55286, 56563, 47650, 54035, 52107, 53358, 51197, 52265, 70176, 88904, 70456, 58402, 112270, 64473, 50856, 58673, 71495, 73949, 87068, 91017, 55512, 50558, 90856, 82440, 64990, 66171, 69218, 60771, 59417, 55286, 79755, 74953, NA, 73446, 65486, 63749, 73635, 62211, 88971, 85918, 97604, 79473, 109327, NA, 125611, 57318, 71015, 65238, 62409, 54192, 59688, NA, NA, 49644, 70296, 33993, 65387, 71575, 54622, 170426, 145332, 101518, 52107, 56157, 47260, NA, 113850, 108092, 70456, 58673, 56776, 60623, 81498, 88506, 64196, 68499, 52941, NA, 59788, 145543, 96539, 61516, 90637, NA, 67101, 59124, 54401, 58673, 81997, 54686, 63430, 74576, 68443, 68499, 50563, 46478, 51607, 56716, 69897, 76460, 77966, NA, NA, 58557, 49084, 54810, 64493, 71854, 67660, 54748, 48849, 49214, 55964, 127836, 84653, 64121, 44384, 74200, 65486, 49683, 57318, 86867, 76836, 84653, 55286, 60230, 57318, 76460, 58673, 81111, 73035, 86129, 79688, 83177, 85860, 79284, 65610, 63005, 61814, 58402, 73635, 52733, 55964, 61814, 98403, 61516, NA, 62260, 108577, 90283, NA, 71575, 72899, 60161, 65089, 69338, 84284, 64706, 66077, 58092, 67324, 67660, 69338, 76083, 95473, 46087, 63328, 69338, NA, 75518, NA, 63997, 86621, NA, 86867, 72510, 44971, 79284, 60878, NA, NA, 48139, 60623, 58221, 72796, 66104, 82440, 65486, 58402, 54154, 45383, 58402, 86867, 59726, 84100, 73425, 96183, NA, 67164, 61516, 94864, 175674, 57735, 58221, NA, 82440, 51169, 65066, 59124, 102409, 109095, 67660, 91211, 59169, 52733, 64990, 57318, 50677, 65198, NA, 61888, 61020, 59425, 42682, 48432, 74262, NA, 95102, 48198, 54724, 60771, 68778, 46087, 116083, 50465, 76460, 69338, 63005, 43798, 53810, 39369, 33987, 73446, 67101, 76041, 99251, 43240, 54463, 62579, 68219, 70456, NA, NA, 96457, 65131, 57318, 67324, 77966, 62012, 68688, 80022, 78343, 64990, 67324, 92563, 59253, 60771, 45696, 67660, 64990, 59124, 77401, 55625, 54109, 127993, 65486, 63005, 68858, NA, 120363, NA, 52941, 68965, 60013, 57526, 115761, 76460, 131707, 94674, 52420, 68858, 97663, 74786, 52941, 75706, 65131, 53984, NA, 119642, 52107, 71015, NA, 98213, 76878, 80521, 73635, 79912, NA, 68499, 45500, NA, 105585, 63749, 91744, 57714, NA, 78896, 74157, 58673, 76460, 113246, 93467, 155263, 74200, 53358, 82685, 77715, 61064, 58221, 86424, 100915, 127652, 63005, 57995, NA, 63005, 63005, 66461, 65797, 72462, 94408, 60689, 88198, 98506, 61218, 85206, 80292, 65267, 77087, 73949, 63997, 32678, 33993, 37208, 88342, 43519, 78029, 74576, 56415, 79389, 70169, 66821, 64990, 53358, 66821
#> $ tuit_grad_res <dbl> 8130, 7588, 11700, 9834, 10470, 9072, 9540, 9936, 5598, 18530, 7146, 8436, 11700, 10810, 11372, 8956, 7680, 7379, 4626, 4932, 4594, 15678, 13152, 5022, 16224, 11430, 17500, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 6738, 11220, 11220, 11220, 11220, 11220, 26896, 8150, 16722, 14940, 17550, 17532, 6738, 13320, 12888, 10452, 11232, 15696, 16713, 44068, 31300, 10980, 20100, 6738, 25470, 6738, 23310, 6738, 27594, 36657, 6738, 41592, 34680, 4410, 6714, 9983, 10836, 12567, 9628, 45288, 11250, 20720, 14940, 6496, 13726, 16632, 12060, 15660, 17730, 20745, 12822, 6497, 6497, 30960, 8190, 28422, 17100, 28800, 13410, 17820, 13050, 6916, 16296, 8019, 5467, 22338, 8912, 16725, 10770, 13320, 21964, 34200, 8570, 18373, 10755, 18996, 9630, 8350, 14076, 16768, 12269, 10584, 7088, 3402, 11736, 5512, 5706, 39800, 13452, 3330, 5187, 6636, 8492, 8910, 4374, 3996, 18600, 15288, 17190, 6232, 6789, 6460, 8851, 10800, 15300, 14328, 18960, 6936, 29730, 7368, 13263, 17168, 7466, 29784, 14310, 18594, 9662, 10962, 15372, 12906, 11858, 50424, 6408, 14845, 24750, 12780, 18996, 17993, 13302, 15100, 10524, 6312, 7767, 11663, 6750, 11460, 7872, 35492, 8497, 7128, 6648, 13000, 16403, 11070, 11700, 8474, 8856, 6996, 16020, 17964, 9990, 5922, 3398, 10068, 9480, 9306, 9670, 12000, 6218, 10764, 10085, 8250, 5173, 10950, 11904, 5670, 6552, 11400, 9132, 6593, 5703, 7234, 5686, 6490, 6540, 5336, 5511, 49030, 7524, 8460, 6840, 24468, 13140, 7182, 7092, 8100, 50410, 15840, 8244, 11718, 7074, 12167, 6858, 14106, 10530, 11610, 22420, 33800, 27216, 49176, 48507, 1675, 13736, 42800, 14793, 3186, 14304, 13524, 16863, 22633, 2520, 20556, 29640, 14994, 32333, 24120, 25344, 2700, 25128, 12232, 12942, 27666, 15120, 13712, 12720, 19116, 21466, 16764, 11300, 9959, 16338, 12869, 10710, 6927, 14746, 13312, 12778, 9630, 8550, 8532, 7185, 16240, 8820, 7373, 8100, 24386, 14076, 6885, 6720, 5269, 10080, 6298, 7141, 7644, 6858, 10206, 7780, 7549, 8400, 7575, 6683, 8496, 7200, 12654, 15672, 9405, 4551, 8025, 15030, 19350, 6307, 4644, 48950, 12690, 8400, 4135, 9810, 3600, 4649, 7134, 14038, 3600, 4968, 4752, 16000, 13560, 18810, 9108, 9810, 16720, 15660, 21564, 18000, 15102, 12960, 10196, 13156, 24156, 10464, 19008, 14545, 22239, 16536, 19476, 33328, 10686, 12024, 10998, 3934, 4418, 7780, 4088, 14376, 3026, 37623, 32517, 14310, 29286, 26460, 43552, 29500, 10130, 10130, 10130, 16380, 15624, 32160, 22320, 19116, 27087, 13536, 28272, 17505, 14040, 15156, 19170, 13500, 13230, 42610, 39936, 21870, 10350, 28680, 13482, 41804, 12240, 13194, 14382, 16182, 15930, 15888, 10870, 10870, 10870, 10870, 10870, 10870, 10870, 10870, 10870, 34632, 16200, 17483, 19800, 4744, 11326, 4656, 12654, 3371, 7722, 9900, 13770, 4545, 9643, 4252, 5117, 4647, 8088, 4448, 3639, 11520, 11194, 37520, 9450, 4348, 12100, 6865, 7185, 5570, 7731, 5713, 12697, 7632, 11250, 42576, 12790, 9565, 16020, 14400, 16008, 11090, 11349, 10200, 10260, 12890, 8964, 10825, 10620, 11560, 9510, 12600, 13166, 18636, 18936, 11970, 13474, 10908, 8492, 9270, 20772, 6043, 3899, 5033, 13734, 4886, 4464, 5316, 22230, 10762, 15504, 15000, 12150, 14391, 30421, 13248, 17496, 14292, 19560, 13140, 11592, 11520, 11592, 16261, 16254, 11592, 7824, 32184, 22212, 16200, 17370, 11934, 11772, 13248, 11592, 23020, 43320, 25560, 10106, 9300, 12060, 19964, 32286, 15858, 12240, 25000, 11352, 12672, 11592, 11592, 15786, 17917, 15840, 11592, 24800, 22368, 13260, 26832, 11826, 8880, 11796, 9180, 7542, 3750, 15075, 70, 8826, 7650, 12398, 13320, 14312, 6840, 7516, 8300, 20160, 8580, 22600, 5700, 18576, 7992, 9024, 11376, 18956, 8820, 7974, 8100, 11044, 8502, 8380, 9200, 6426, 6870, 19890, 3783, 28494, 12240, 3568, 15408, 30200, 3619, 3630, 16481, 7074, 6602, 5798, 7956, 15930, 6048, 3350, 20115, 14940, 3849, 5450, 15390, 4362, 35712, 25092, 20934, 5139, 15570, 40896, 10350, 4896, 6167, 3672, 3228, 5784, 7141, 11300, 12418, 4497, 4896, 26640, 5186, 1600, 5400, 4522, 10620, 4402, 6680, 7280, 5323, 7192, 6473, 7677, 13412, 14436, 17073, 15096, 9000, 12726, 13715, 10628, 10776, 9648, 8051, 8820, 6588, 16920, 8736, 20304, 12467, 10976, 15026, 13914, 10953, 16457, 18202, 25381, 13800, 19353, 11224, 15207, 9582, 11952, 5770, 9000, 10176, 12015, 10539, 10170, 16164, 10305, 4860, 19350, 7936, 7640, 7640, 10387, 7640, 7640, 4338, 2652, 2652, 2652, 9208, 10692, 11160, 6738, 11880, 6738, 6500, 6974, 6738, 9000, 5144
#> $ fee_grad_res <dbl> 1236, 0, 1390, 508, 0, 1624, 840, 640, 1226, 610, 802, 1385, 410, 696, 1011, 451, 1604, 971, 1292, 1026, 1287, 500, 0, 918, 220, 710, 150, 3603, 1385, 1256, 1138, 1595, 1568, 951, 841, 1088, 1092, 988, 911, 1115, 1428, 2017, 1844, 1463, 2118, 1865, 370, 0, 300, 40, 85, 500, 1737, 180, 930, 135, 0, 80, 619, 380, 120, 0, 172, 1612, 354, 1012, 50, 1946, 0, 0, 1916, 713, 400, 2488, 1738, 0, 1774, 840, 2088, 303, 0, 184, 2510, 4460, 2270, 80, 510, 200, 720, 0, 828, 4722, 4801, 792, 50, 690, 526, 45, 0, 0, 100, 1956, 1294, 1857, 1190, 250, 2185, 200, 1967, 0, 1200, 1016, 1797, 802, 400, 0, 0, 2078, 0, 0, 450, 80, 1974, 1602, 400, 1454, 1850, 3180, 2200, 1376, 2022, 2092, 2270, 0, 2116, 1962, 0, 880, 130, 2208, 1713, 2070, 120, 0, 260, 360, 330, 2769, 250, 1900, 3080, 720, 1504, 500, 100, 848, 0, 390, 0, 0, 1981, 440, 1389, 100, 0, 100, 313, 327, 375, 450, 4059, 1642, 3558, 0, 200, 960, 0, 588, 500, 200, 595, 0, 930, 428, 0, 1075, 1501, 0, 280, 0, 240, 1884, 657, 0, 958, 406, 862, 0, 1514, 0, 0, 110, 905, 0, 300, 300, 150, 0, 2755, 2483, 1872, 1064, 2166, 2172, 1829, 3996, 3939, 1980, 1142, 0, 830, 682, 1508, 1924, 2448, 210, 1800, 60, 270, 1538, 1404, 0, 1512, 60, 0, 40, 0, 580, 90, 710, 88, 8563, 0, 30, 0, 2556, 375, 2089, 355, 280, 4671, 162, 195, 405, 52, 0, 60, 2664, 690, 0, 790, 0, 1235, 0, 766, 150, 328, 0, 722, 432, 0, 350, 310, 290, 1757, 923, 0, 0, 0, 0, 669, 1495, 0, 883, 0, 214, 360, 777, 684, 1277, 0, 120, 120, 100, 20, 600, 0, 110, 300, 1095, 701, 126, 396, 324, 660, 0, 2342, 0, 490, 546, 1101, 910, 330, 0, 100, 1758, 525, 1203, 1441, 1676, 0, 1131, 532, 535, 1175, 175, 0, 630, 50, 400, 198, 870, 910, 968, 2718, 1944, 3316, 700, 1676, 2806, 3131, 450, 2097, 60, 1186, 3214, 0, 1386, 2083, 1598, 1526, 853, 0, 1624, 1335, 970, 724, 650, 790, 2002, 85, 308, 432, 430, 470, 860, 491, 970, 490, 111, 290, 1904, 540, 0, 620, 950, 160, 0, 276, 2432, 100, 350, 1000, 300, 274, 50, 0, 814, 351, 180, 340, 1824, 2051, 2477, 1696, 711, 1284, 1063, 515, 480, 1242, 1000, 550, 200, 2977, 549, 2632, 0, 2162, 50, 0, 105, 2902, 1963, 3026, 2636, 2477, 2484, 2595, 2285, 0, 536, 490, 0, 2844, 720, 1375, 1458, 962, 1405, 0, 0, 1765, 0, 34, 1678, 114, 50, 685, 0, 0, 918, 420, 0, 638, 0, 500, 450, 865, 0, 0, 1555, 176, 300, 100, 0, 12, 410, 1905, 2668, 751, 673, 2702, 2070, 3283, 306, 1110, 490, 1434, 0, 180, 1651, 1852, 213, 1317, 0, 1710, 0, 263, 2573, 90, 3916, 130, 468, 5096, 138, 840, 0, 230, 550, 0, 450, 274, 2923, 570, 1030, 0, 1314, 1415, 0, 948, 3318, 990, 0, 550, 50, 600, 3384, 3771, 890, 100, 0, 2399, 300, 1728, 0, 0, 0, 0, 1566, 100, 700, 40, 0, 12914, 856, 0, 400, 120, 300, 0, 1042, 1473, 730, 200, 260, 0, 0, 1379, 0, 70, 30, 1643, 1260, 1776, 1790, 1394, 1040, 1171, 0, 20, 0, 2612, 3006, 350, 2732, 800, 0, 1440, 2146, 2485, 1360, 1166, 1192, 982, 1575, 1958, 2367, 0, 1450, 2029, 1733, 816, 2782, 540, 150, 324, 2184, 680, 5664, 960, 1531, 1801, 2437, 2141, 3120, 1678, 0, 0, 1126, 1480, 48, 1915, 5118, 2125, 2364, 1180, 1947, 0, 756, 954, 630, 1054, 912, 182, 0, 2176, 1916, 5258, 500, 60, 3096, 35, 1104, 379, 92, 3030, 180, 2744, 1190, 2065, 2167, 2654, 0, 841, 424, 200, 100, 0, 765, 1529, 1059, 921, 0, 1734, 0, 700, 0, 0, 120, 0, 0, 0, 0, 0, 1271, 1122, 1402, 1066, 1396, 1335, 900, 900, 900, 794, 300, 300, 1911, 500, 907, 290, 1987, 1075, 0, 1690
#> $ tuit_grad_nres <dbl> 16260, 17294, 11700, 21830, 26950, 27216, 9540, 20592, 11196, 18530, 14292, 17233, 11700, 23480, 31124, 17781, 17400, 18842, 9252, 9864, 9188, 15678, 13152, 7452, 16224, 11430, 17500, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 15666, 26322, 26322, 26322, 26322, 26322, 26896, 8150, 16722, 14940, 17550, 17532, 15666, 13320, 12888, 10452, 11232, 15696, 16713, 44068, 31300, 10980, 20100, 15666, 25470, 15666, 23310, 15666, 27594, 36657, 15666, 41592, 34680, 10332, 22374, 20153, 28656, 12567, 23604, 45288, 11250, 20720, 14940, 18102, 34762, 16632, 12060, 15660, 17730, 20745, 12822, 18102, 18102, 30960, 8190, 28422, 17100, 28800, 13410, 17820, 13050, 25759, 16296, 22108, 16695, 22338, 21393, 16725, 27335, 13320, 21964, 34200, 19585, 18373, 10755, 18996, 9630, 19048, 14076, 16768, 12269, 10584, 22166, 13590, 11736, 13507, 11952, 39800, 27872, 13248, 18486, 26518, 24090, 8910, 15750, 15498, 18600, 36768, 17190, 20682, 20870, 21268, 8851, 10800, 15300, 14328, 18960, 16656, 29730, 14736, 22217, 17168, 15038, 29784, 14310, 18594, 9662, 10962, 15372, 12906, 20426, 50424, 12816, 14845, 24750, 12780, 18996, 17993, 13302, 15100, 26310, 11156, 11651, 11663, 6750, 11460, 7872, 35492, 16691, 13986, 15661, 13000, 16403, 11070, 11700, 21786, 26460, 6996, 16020, 17964, 9990, 18414, 9676, 10068, 22176, 9306, 21828, 12000, 16302, 10764, 10085, 16786, 12704, 10950, 11904, 5670, 6552, 16320, 9132, 19478, 16778, 20673, 16617, 18590, 19017, 5336, 19239, 49030, 24498, 8460, 18468, 24468, 19062, 12384, 9108, 8100, 50410, 15840, 11862, 25272, 13860, 12167, 12060, 14106, 10530, 11610, 22420, 33800, 27216, 49176, 48507, 1675, 13736, 42800, 14793, 3186, 25853, 29644, 32913, 22633, 4140, 20556, 29640, 27068, 32333, 24120, 25344, 2700, 25128, 18216, 12942, 27666, 27840, 13712, 12720, 19116, 43346, 32940, 19998, 14922, 24648, 24517, 10710, 6927, 31939, 28195, 12778, 9630, 8550, 8532, 14370, 25120, 8820, 11201, 8100, 24386, 14076, 6885, 10120, 5269, 10080, 6298, 7141, 21912, 6858, 10206, 20900, 16419, 8400, 7575, 13366, 8496, 7200, 12654, 15672, 9405, 9103, 8025, 15030, 19350, 11767, 9324, 48950, 12690, 8400, 18742, 9810, 7200, 12987, 20412, 14038, 7200, 18878, 18662, 16000, 13560, 18810, 10494, 9810, 16720, 15660, 21564, 18000, 15102, 12960, 17966, 17831, 24156, 15837, 28092, 14545, 22239, 28128, 19476, 33328, 16449, 12024, 17856, 9880, 7552, 22643, 14254, 14376, 8730, 37623, 32517, 14310, 29286, 26460, 43552, 29500, 18720, 18720, 18720, 16380, 15624, 32160, 22320, 19116, 27087, 13536, 28272, 17505, 14040, 15156, 19170, 13500, 13230, 42610, 39936, 21870, 10350, 28680, 13482, 41804, 12240, 13194, 14382, 16182, 15930, 15888, 22210, 22210, 22210, 22210, 22210, 22210, 22210, 22210, 22210, 34632, 16200, 17483, 19800, 17913, 11326, 17547, 12654, 14219, 7722, 9900, 13770, 16950, 26854, 17423, 18566, 17347, 22610, 16667, 13896, 11520, 11194, 37520, 9450, 14755, 12100, 6865, 19184, 14873, 13237, 5713, 12697, 13284, 11250, 42576, 24532, 16297, 16020, 14400, 16008, 19362, 11349, 10200, 10260, 29604, 8964, 10825, 10620, 32008, 17502, 12600, 23502, 18636, 18936, 11970, 22890, 10908, 12992, 9270, 20772, 15010, 8813, 19801, 13734, 18989, 10674, 11652, 22230, 13354, 15504, 15000, 21799, 24759, 30421, 20736, 17496, 17892, 19560, 13140, 17400, 11520, 17400, 16261, 16254, 17400, 7824, 32184, 22212, 16200, 17370, 11934, 11772, 13248, 17400, 23020, 43320, 25560, 17636, 9300, 12060, 34266, 32286, 15858, 12240, 25000, 11352, 12672, 17400, 17400, 21636, 17917, 15840, 17400, 24800, 22368, 13260, 26832, 11826, 8880, 24206, 9180, 7542, 3750, 15075, 70, 18424, 7650, 27008, 24144, 27570, 6840, 14449, 22280, 20160, 8580, 22600, 5700, 18576, 22248, 9024, 11376, 18956, 17604, 22086, 24218, 29232, 14262, 20020, 23720, 6426, 6870, 19890, 11128, 28494, 12240, 10912, 15408, 30200, 11564, 10974, 16481, 15696, 13046, 13142, 17100, 15930, 13392, 10694, 20115, 14940, 5019, 12794, 15390, 12390, 35712, 25092, 20934, 12483, 15570, 40896, 10350, 12240, 14327, 11015, 10572, 15953, 15638, 21518, 24150, 12326, 12294, 26640, 20785, 8244, 12744, 11867, 10620, 5081, 6680, 22861, 18632, 17718, 22848, 16161, 13412, 14436, 17073, 38160, 24686, 12726, 13715, 29306, 10776, 26688, 8051, 8820, 15462, 16920, 25548, 20304, 25095, 22479, 25168, 13914, 25438, 16457, 18202, 25381, 13800, 19353, 24656, 27255, 19866, 11952, 14114, 23238, 10176, 12015, 10539, 10170, 16164, 10305, 4860, 19350, 7936, 16771, 16771, 23424, 16771, 16771, 12978, 2652, 2652, 2652, 28010, 10692, 11160, 15666, 11880, 15666, 6500, 28170, 15666, 9000, 17544
#> $ fee_grad_nres <dbl> 1236, 0, 1390, 508, 0, 1624, 840, 640, 1226, 610, 802, 1727, 410, 696, 1011, 513, 1604, 971, 1292, 1026, 1287, 500, 0, 918, 220, 710, 150, 3603, 1385, 1256, 1138, 1595, 1568, 951, 841, 1088, 1092, 988, 911, 1115, 1428, 2017, 1844, 1463, 2118, 1865, 370, 0, 300, 40, 85, 500, 1737, 180, 930, 135, 0, 80, 619, 380, 120, 0, 172, 1612, 354, 1012, 50, 1946, 0, 0, 1916, 713, 400, 2488, 1738, 0, 1774, 840, 2088, 303, 0, 184, 2510, 5654, 2270, 80, 510, 200, 720, 0, 828, 5917, 5996, 792, 50, 690, 526, 45, 0, 0, 100, 2898, 1294, 2561, 1751, 250, 2809, 200, 2795, 0, 1200, 1016, 2348, 802, 400, 0, 0, 2078, 0, 0, 450, 80, 2728, 1602, 400, 1454, 1850, 3180, 2200, 1376, 2022, 2092, 2270, 0, 2116, 1962, 0, 880, 130, 2208, 1713, 2070, 120, 0, 260, 360, 330, 2769, 250, 1900, 3080, 720, 1504, 500, 100, 848, 0, 390, 0, 0, 1981, 440, 1389, 100, 0, 100, 313, 327, 375, 450, 4059, 1782, 3558, 0, 200, 960, 0, 588, 500, 200, 595, 0, 930, 428, 0, 1075, 1501, 0, 280, 0, 240, 1884, 657, 0, 958, 406, 862, 0, 1514, 0, 0, 110, 905, 0, 300, 300, 150, 0, 19690, 2483, 1872, 1064, 2166, 2172, 1829, 13996, 3939, 1980, 1142, 0, 830, 682, 1508, 1924, 2448, 210, 1800, 60, 270, 1538, 1404, 0, 1512, 60, 0, 40, 0, 580, 90, 710, 88, 8563, 0, 30, 0, 2556, 375, 2089, 355, 280, 4671, 162, 195, 405, 52, 0, 60, 2664, 690, 0, 790, 0, 1235, 0, 766, 150, 328, 0, 722, 432, 0, 350, 310, 290, 1757, 923, 0, 0, 0, 0, 669, 1495, 0, 883, 0, 214, 360, 777, 684, 1277, 0, 120, 10473, 100, 20, 600, 0, 110, 300, 1095, 701, 126, 396, 324, 660, 0, 2342, 0, 490, 546, 1101, 910, 330, 0, 100, 1812, 525, 1203, 1441, 1676, 0, 1131, 532, 535, 1175, 175, 0, 630, 50, 400, 198, 870, 910, 968, 2718, 1944, 3316, 700, 1676, 2806, 3131, 450, 2097, 60, 1186, 3214, 0, 1386, 2083, 1598, 1526, 853, 0, 1624, 1335, 970, 724, 650, 790, 2002, 85, 308, 432, 430, 470, 860, 491, 970, 490, 111, 290, 1904, 540, 0, 620, 950, 160, 0, 276, 2432, 100, 350, 1000, 300, 274, 50, 0, 814, 351, 180, 340, 1824, 2051, 2477, 1696, 711, 1284, 1063, 515, 480, 1242, 1000, 550, 200, 2977, 549, 2632, 0, 2162, 50, 0, 105, 2902, 1963, 3026, 2636, 2477, 2484, 2595, 2285, 0, 536, 490, 0, 2844, 720, 1375, 1458, 962, 1405, 0, 0, 1765, 0, 34, 1678, 114, 50, 685, 0, 0, 918, 420, 0, 638, 0, 500, 450, 865, 0, 0, 1555, 176, 300, 100, 0, 12, 410, 1905, 2668, 751, 673, 2702, 2070, 3283, 306, 1110, 490, 1434, 0, 180, 1651, 1852, 213, 1317, 0, 1710, 0, 263, 2861, 90, 5119, 130, 468, 6875, 138, 840, 0, 230, 550, 0, 450, 274, 3825, 570, 1030, 0, 1452, 1415, 0, 948, 3318, 990, 0, 550, 50, 600, 3672, 4930, 890, 100, 0, 2615, 300, 1728, 0, 0, 0, 0, 1566, 100, 700, 40, 0, 32888, 856, 0, 400, 120, 300, 0, 1042, 1473, 730, 200, 260, 0, 0, 1379, 0, 70, 30, 1643, 1260, 1776, 2020, 1394, 1040, 1171, 0, 20, 0, 2612, 3006, 350, 3161, 800, 0, 1440, 2146, 2485, 1360, 1166, 1192, 982, 1575, 1958, 2796, 0, 1450, 2029, 1733, 816, 2782, 540, 150, 324, 2184, 680, 5664, 960, 1531, 1801, 2437, 2141, 3120, 1678, 0, 0, 1126, 1480, 48, 1915, 5666, 2125, 2364, 1180, 1947, 0, 756, 954, 630, 1054, 912, 182, 0, 2176, 1916, 5814, 500, 60, 3096, 35, 1608, 379, 92, 3030, 180, 3312, 1190, 2669, 2792, 3336, 0, 841, 424, 200, 100, 0, 765, 1529, 1059, 921, 0, 1946, 0, 700, 0, 0, 120, 0, 0, 0, 0, 0, 1271, 1122, 1402, 1066, 1396, 1335, 900, 900, 900, 794, 300, 300, 1911, 500, 907, 290, 3046, 1075, 0, 1690
#> $ books_supplies <dbl> 1600, 1200, 1500, 1688, 1200, 1200, 1800, 1020, 1500, 1000, 1129, 1400, 1220, 1103, 800, 1000, 1715, 1046, 1137, 1410, 1200, 1200, 800, 1600, 1792, 1790, 1791, 1848, 1898, 1500, 1791, 1650, 1792, 1764, 1792, 1898, 1500, 1898, 1898, 1600, 1792, 1601, 1766, 1636, 1716, 1541, 1500, 1700, 1790, 1854, 1920, 1792, 1660, 1791, 1791, 1900, 1592, 1844, 1791, 1791, 1500, 1790, 1775, 1818, 1800, 1900, 1600, 1899, 1791, 1107, 1790, 1200, 1800, 1800, 1800, 1800, 1800, 1000, 1200, 1200, 1800, 1000, 1500, 1300, 850, 1150, 972, 1000, 800, 1200, 1000, 1400, 1300, 800, 1800, 800, 1600, 1275, 1040, 1500, 800, 1152, 1400, 1138, 1320, 1200, 1590, 1244, 1210, 1320, 2000, 930, 1200, 1500, 1030, 1250, 1720, 1200, 850, 1200, 1600, 1500, 1200, 1298, 1300, 1222, 1270, 1224, 800, 1400, 1500, 1200, 1006, 1400, 1200, 1500, 1600, 952, 1200, 1200, 1000, 1214, 1200, 1000, 1200, 1200, 1104, 150, 1000, 900, 1400, 1510, 942, 1500, 1500, 1200, 1000, 1350, 1200, 1000, 1400, 1620, 2400, 1000, 1500, 1200, 1200, 1200, 800, 1200, 1100, 840, 900, 1200, 1200, 1000, 1000, 1250, 1140, 1170, 1204, 1380, 1200, 1200, 950, 995, 950, 1280, 1200, 1560, 1200, 1000, 1080, 1500, 1080, 986, 856, 1490, 1000, 2547, 1000, 1000, 1000, 792, 1100, 1200, 1200, 1000, 1160, 1500, 1220, 1220, 1220, 1220, 1220, 1240, 1220, 1200, 1000, 1200, 1200, 800, 1600, 2200, 1400, 1200, 1220, 1250, 0, 1200, 2500, 1300, 1300, 1200, 1000, 1000, 1100, 1260, 1250, 1000, 1000, 800, 1500, 800, 1150, 1000, 1200, 1000, 800, 1000, 1200, 1280, 1000, 1200, 1200, 1240, 1000, 1368, 1100, 1000, 904, 880, 1000, 1200, 1000, 1453, 1048, 1076, 1300, 1000, 764, 1350, 1000, 800, 1196, 948, 1200, 1186, 2000, 480, 1500, 1000, 600, 1200, 1300, 1000, 1000, 1200, 1200, 1556, 1200, 1000, 2300, 1200, 1400, 1100, 1200, 1200, 3300, 1040, 1000, 1200, 1000, 1000, 1200, 1200, 400, 1800, 1485, 1200, 502, 1100, 980, 1000, 1200, 1400, 1350, 1600, 1080, 1012, 1040, 1120, 1298, 1300, 1200, 1000, 1200, 1337, 1400, 2100, 1200, 1230, 1300, 1350, 1600, 1200, 1384, 1234, 1300, 2600, 1569, 1500, 1350, 1000, 1200, 1597, 1698, 1600, 950, 1100, 1080, 1298, 1200, 1466, 1020, 1300, 1000, 1416, 1000, 1400, 910, 1364, 1364, 1364, 1200, 1500, 1012, 1000, 1500, 1300, 1300, 2000, 1200, 1000, 1524, 1470, 1200, 1185, 1589, 1070, 1104, 1000, 800, 1100, 1050, 1200, 800, 1200, 1000, 1100, 615, 1200, 1000, 1196, 900, 1037, 1600, 800, 1528, 1500, 1440, 778, 1400, 822, 700, 1600, 1280, 900, 400, 1300, 1160, 1200, 1400, 1442, 1200, 956, 1500, 1082, 1104, 1505, 1500, 1200, 1400, 1400, 2151, 1222, 1100, 1000, 800, 1000, 912, 1582, 1010, 1550, 1200, 1500, 800, 1000, 1240, 1000, 1200, 1100, 1320, 1200, 1216, 1400, 1200, 1100, 1234, 1030, 2000, 1150, 1216, 1200, 1104, 1248, 1000, 1100, 900, 1200, 1600, 1260, 1260, 1500, 714, 1000, 1218, 1200, 1425, 950, 900, 1551, 1122, 1050, 2090, 864, 999, 1144, 1500, 1200, 1200, 1000, 1020, 1000, 1000, 1000, 1700, 1400, 1200, 1066, 900, 1200, 1080, 1100, 1000, 1100, 1000, 1597, 1000, 1488, 1840, 1280, 1200, 1500, 2000, 1300, 1200, 1200, 1550, 1000, 1100, 1500, 1200, 1300, 1500, 1200, 1300, 1500, 940, 1200, 1400, 2000, 1400, 1060, 1159, 1308, 2200, 1023, 1160, 1000, 950, 1200, 1550, 1400, 1600, 1000, 1400, 1500, 1090, 1420, 1200, 1400, 1415, 1540, 1400, 1598, 1400, 2300, 2300, 1471, 1250, 1250, 1200, 1444, 1274, 868, 1260, 1200, 1400, 1400, 1000, 1064, 1210, 1200, 1300, 1200, 1000, 1456, 1550, 1300, 1350, 1000, 1200, 1300, 800, 1050, 1094, 1000, 1300, 800, 1298, 1192, 820, 1200, 1344, 1054, 1206, 662, 1200, 1216, 1292, 1050, 1000, 1524, 1200, 1050, 1650, 1000, 812, 1600, 810, 976, 1232, 1200, 1000, 1000, 1500, 1200, 1350, 1000, 1000, 1200, 1100, 990, 1771, 1000, 1200, 1000, 1000, 1500, 1210, 2804, 1294, 1000, 900, 1092, 1000, 825, 1000, 1500, 960, 825, 906, 840, 1000, 900, 625, 700, 1078, 1600, 800, 950, 800, 1008, 1000, 400, 1000, 800, 500, 370, 1200, 1700, 1700, 1700, 1220, 1400, 1800, 1764, 1600, 1339, 200, 1200, 1898, 1046, 2000
#> $ roomboard_off <dbl> 8830, 11682, 9600, 9603, 13050, 12898, 8000, 8980, 7284, 9850, 5815, 12080, 15060, 9216, 11300, 9262, 9406, 10332, 8910, 12634, 7054, 6756, 2500, 6915, 12494, 12370, 12492, 12507, 13780, 10900, 13770, 12588, 11360, 12888, 12492, 13882, 13884, 12910, 13882, 11358, 12492, 8606, 9814, 10667, 9008, 10131, 12268, 12400, 4968, 13293, 13200, 13500, 12638, 12492, 12492, 12298, 11104, 12916, 12492, 12492, 14330, 12492, 12492, 12050, 12492, 13882, 13990, 13882, 12492, 12240, 13882, 14348, 12492, 9693, 11205, 10400, 11788, 8910, 9693, 12021, 9694, 12265, 8520, 10503, 12436, 13860, 11986, 11468, 13850, 10462, 10750, 9698, 11884, 12068, 6000, 15698, 13040, 12500, 11440, 11400, 11608, 9764, 10826, 9636, 11364, 13610, 11837, 10680, 9910, 16740, 8544, 16490, 9934, 19125, 8776, 11530, 11680, 9700, 13997, 12326, 3500, 6500, 9354, 10622, 9684, 11750, 9030, 13486, 13640, 7672, 13150, 9800, 8032, 8540, 9258, 6849, 12478, 13030, 17362, 8974, 8280, 8354, 8350, 3858, 10010, 5850, 13387, 9546, 5500, 10868, 10882, 10260, 8082, 8000, 7000, 11500, 7500, 15300, 8565, 8980, 10776, 15489, 6588, 12660, 6111, 7750, 8600, 16699, 7200, 7206, 10186, 9211, 9580, 6000, 4000, 12947, 8000, 6812, 9920, 9696, 7170, 7010, 7400, 8900, 9060, 8356, 8588, 5440, 9470, 8120, 7970, 8392, 7710, 7590, 9610, 11169, 7662, 10881, 7025, 5955, 6296, 10252, 10575, 11820, 3600, 6750, 8400, 7713, 15772, 6516, 9074, 9073, 9074, 9073, 9072, 9714, 9073, 13844, 10164, 7200, 9980, 6500, 14200, 13114, 6000, 11240, 10255, 7870, 15430, 13966, 11876, 7500, 11352, 4630, 6012, 11660, 3500, 15130, 10200, 14870, 11330, 12200, 8000, 8450, 8881, 6380, 5150, 11897, 9200, 15050, 10310, 14500, 11890, 10000, 14882, 9730, 13410, 5400, 10464, 7346, 6324, 9514, 7400, 7780, 8810, 10107, 10872, 9784, 8064, 8706, 6252, 9185, 10040, 9270, 9134, 9561, 17358, 6600, 8500, 9894, 9610, 9377, 4120, 8230, 7700, 8700, 9010, 7686, 8460, 9356, 9000, 7374, 6100, 10002, 7394, 9812, 9418, 10000, 5900, 9488, 8350, 6290, 5104, 7998, 9000, 6521, 8558, 6400, 10125, 10640, 8508, 8288, 15596, 9516, 2050, 8826, 10350, 7164, 8648, 9774, 8354, 7110, 9190, 10558, 12200, 11700, 9514, 9708, 9990, 13500, 10894, 10575, 13000, 9882, 9475, 12446, 10973, 8967, 10964, 10300, 10849, 9600, 17934, 7500, 14350, 11942, 5670, 10800, 7496, 9108, 9472, 8944, 12800, 8224, 9720, 12196, 8000, 9892, 9600, 17010, 13900, 13713, 13713, 13713, 11570, 10000, 11924, 17315, 14400, 10230, 12970, 25000, 15010, 13250, 8096, 9436, 9900, 13380, 13000, 17578, 15558, 9300, 18312, 7222, 12500, 7000, 11463, 12356, 6500, 11740, 12450, 9750, 8090, 11241, 12900, 12982, 12000, 13390, 11600, 11948, 15217, 12865, 10036, 13260, 8380, 10760, 9241, 11495, 8070, 5400, 11600, 6244, 7153, 12218, 9823, 8744, 9636, 10635, 8624, 8208, 10700, 7300, 13404, 7000, 10100, 7292, 8264, 7856, 8136, 12342, 5500, 8882, 7446, 11000, 14298, 12102, 12000, 12680, 5795, 11250, 10720, 6176, 7760, 6300, 12454, 4150, 9000, 6360, 11706, 12268, 10200, 7514, 11508, 6450, 8538, 11376, 11730, 8990, 8136, 5400, 9772, 6378, 8840, 9814, 10280, 5544, 5112, 11338, 8930, 10528, 8650, 11874, 9807, 11822, 12200, 7556, 9699, 8998, 5100, 8912, 10000, 10524, 10784, 11042, 11146, 13328, 14367, 11760, 7200, 11990, 4000, 12000, 10062, 12044, 7500, 7100, 12690, 9268, 10000, 12858, 11230, 14536, 3150, 12880, 11000, 9400, 9212, 9504, 8080, 12336, 13093, 7090, 12860, 8190, 8618, 10460, 9000, 6700, 13650, 9586, 10450, 9990, 9050, 5905, 10897, 9144, 9892, 10540, 7928, 7464, 8630, 8008, 9711, 11330, 7508, 8700, 7690, 9980, 7952, 5090, 7880, 5000, 9153, 8246, 9100, 10238, 7996, 6610, 8750, 8500, 9400, 9310, 8216, 10576, 7204, 9114, 10692, 8500, 9532, 7780, 8973, 9704, 8720, 7996, 11067, 10794, 7550, 6910, 10332, 7590, 8012, 7960, 7872, 7355, 13750, 11112, 10090, 8720, 4000, 8700, 13694, 8868, 7260, 9710, 7466, 10368, 8410, 10070, 10190, 9496, 9970, 12000, 9558, 12974, 9081, 6885, 11000, 8582, 7448, 7500, 7880, 5960, 9936, 8000, 7904, 10576, 12920, 10000, 11382, 7965, 8000, 12186, 11700, 9334, 8046, 10120, 11118, 13430, 10864, 9990, 8720, 11280, 10726, 9648, 10941, 11158, 7800, 10330, 9100, 11499, 11356, 14625, 10524, 9585, 8426, 8340, 7850, 6517, 6718, 10280, 8370, 5664, 3750, 12160, 8510, 7538, 7600, 10030, 7350, 7600, 10320, 8000, 8000, 8000, 9460, 8936, 11104, 12826, 11448, 15450, 6000, 9672, 13882, 17654, 13128
#> $ oth_expense_off <dbl> 3090, 4886, 1600, 3578, 4116, 5664, 4700, 3180, 2800, 5498, 5227, 4250, 4160, 4708, 5200, 5070, 5213, 4104, 5202, 4766, 5471, 2414, 2850, 6939, 4158, 4158, 4258, 2646, 2924, 2516, 2658, 2716, 2478, 2870, 2658, 2924, 2706, 2934, 2924, 2182, 2658, 5665, 5383, 5140, 5317, 5621, 4100, 4340, 4286, 4239, 4610, 4292, 2444, 4258, 4536, 5382, 3696, 4914, 4245, 4158, 2500, 4158, 4156, 3296, 4158, 2966, 3800, 2925, 4158, 3170, 2924, 1880, 4158, 2763, 5193, 4600, 2294, 1600, 1360, 2634, 3272, 6776, 10208, 3671, 2650, 1730, 2806, 2760, 2500, 3150, 2644, 3972, 2920, 1500, 1800, 921, 5500, 1900, 2660, 7700, 5783, 4970, 4458, 6313, 5718, 3000, 5354, 1626, 3750, 3524, 7272, 3062, 3834, 8010, 5678, 6170, 2552, 4100, 8448, 3000, 2400, 3630, 2100, 3860, 4500, 2500, 4460, 2416, 3260, 6044, 5303, 5654, 3952, 2890, 4994, 6195, 2245, 2899, 2220, 4030, 5921, 3840, 3440, 3520, 2240, 1700, 2364, 2067, 4000, 7000, 3628, 4230, 5538, 2000, 2504, 1600, 3250, 5940, 6261, 2100, 2584, 2532, 6489, 1000, 4479, 3900, 7700, 1450, 4120, 3106, 2941, 2768, 3570, 2800, 1600, 2550, 3200, 6512, 3082, 2308, 3798, 2692, 3000, 1620, 3790, 2430, 3420, 6434, 5924, 2872, 4880, 3470, 3836, 4422, 3070, 3190, 3860, 3122, 4252, 1906, 6341, 3581, 4769, 5432, 6150, 5500, 6700, 3307, 5420, 4635, 3918, 3919, 3992, 3919, 3916, 3971, 3919, 1060, 2200, 2700, 3000, 2600, 4150, 1600, 3706, 3100, 1044, 1670, 5850, 3932, 4045, 2300, 2700, 3290, 2000, 1800, 2400, 1200, 1700, 1950, 1500, 2800, 2700, 1050, 2422, 2200, 1922, 1400, 2956, 1800, 3402, 2550, 2000, 2072, 3075, 3300, 1200, 3200, 4400, 938, 3452, 5448, 2578, 6614, 2890, 4248, 2454, 2368, 3364, 3910, 4464, 3246, 1556, 1756, 5754, 2366, 2500, 4864, 2000, 1200, 8186, 2200, 4000, 2700, 2390, 2746, 2350, 3156, 3060, 6712, 2600, 4200, 5100, 4660, 4400, 4060, 5184, 3570, 6085, 2984, 2400, 3200, 4152, 6338, 4300, 3409, 2575, 3246, 4216, 3448, 4482, 4034, 3408, 8104, 3200, 3757, 2700, 4824, 3630, 3870, 3262, 2772, 5682, 4500, 3100, 2250, 8206, 2245, 5722, 3800, 4121, 2856, 1780, 6600, 3681, 4500, 3550, 3926, 5576, 5400, 6282, 2030, 3013, 2900, 1050, 3983, 375, 5400, 4498, 3912, 5154, 3764, 2650, 5080, 7208, 1950, 1500, 2446, 3096, 4860, 1850, 5302, 5302, 5302, 3000, 3650, 2748, 3096, 1850, 3660, 1400, 2500, 2000, 2425, 3348, 9804, 2100, 1100, 2010, 2000, 4452, 5990, 2920, 3450, 976, 3275, 1400, 2460, 4000, 1400, 2062, 2086, 2632, 3505, 5336, 3332, 2800, 1600, 2284, 3600, 1665, 4666, 2808, 2313, 3286, 4000, 3644, 2600, 2426, 2600, 2850, 2460, 4220, 3404, 3496, 2536, 4667, 2442, 4604, 3296, 2000, 3472, 2400, 2774, 2516, 2490, 3500, 3422, 3400, 3152, 3728, 5122, 4790, 4948, 1900, 5666, 3470, 1750, 1230, 3000, 3582, 3530, 2730, 3700, 2014, 4500, 1800, 5194, 2870, 2706, 1500, 5358, 1200, 4550, 2532, 2784, 2000, 3635, 3890, 2000, 8546, 5496, 4650, 4260, 5433, 3760, 6210, 4524, 2955, 2120, 2520, 2550, 2349, 1680, 3700, 1774, 3252, 2210, 3600, 3140, 1700, 4350, 2082, 3500, 3596, 1800, 4278, 2200, 1125, 2510, 1150, 4750, 1328, 2288, 1000, 2500, 1065, 5783, 1700, 2470, 4788, 2060, 2100, 1518, 6000, 1868, 3000, 3258, 3604, 5934, 2300, 1410, 2520, 2358, 3000, 2500, 3200, 2409, 1600, 3785, 2300, 3770, 3600, 2100, 3977, 3502, 4314, 4111, 4184, 3000, 3935, 5441, 4538, 4750, 3204, 2716, 6440, 3250, 5700, 6606, 5150, 6130, 4512, 4162, 3600, 5666, 5518, 3420, 6000, 3649, 8010, 3350, 3480, 4430, 3140, 3241, 4968, 3200, 2037, 3938, 5534, 6900, 6918, 4178, 5508, 3416, 4300, 2572, 3136, 3030, 1830, 4376, 3300, 2556, 2050, 2460, 4762, 3796, 3000, 2600, 4764, 3454, 3910, 4118, 4768, 5820, 4512, 4310, 4180, 4292, 4044, 4700, 4666, 4866, 4420, 3708, 4256, 4854, 4500, 4800, 3770, 3434, 3678, 5052, 4410, 2174, 2700, 2302, 2025, 3300, 1800, 4908, 4500, 4150, 6274, 770, 2892, 3734, 2975, 2600, 2980, 3120, 2754, 2000, 3180, 3330, 3960, 2703, 3000, 4170, 3542, 3561, 3495, 3180, 3400, 2620, 4065, 5332, 4790, 2800, 3310, 4896, 3520, 4840, 2500, 3150, 2700, 3306, 3300, 4830, 3040, 4800, 4800, 4800, 1780, 2236, 3816, 2668, 4401, 2925, 1000, 3400, 2924, 3282, 1800
#> $ tuitfee_grad_res <dbl> 9366, 7588, 13090, 10342, 10470, 10696, 10380, 10576, 6824, 19140, 7948, 9821, 12110, 11506, 12383, 9407, 9284, 8350, 5918, 5958, 5881, 16178, 13152, 5940, 16444, 12140, 17650, 10341, 8123, 7994, 7876, 8333, 8306, 7689, 7579, 7826, 7830, 7726, 7649, 7853, 8166, 13237, 13064, 12683, 13338, 13085, 27266, 8150, 17022, 14980, 17635, 18032, 8475, 13500, 13818, 10587, 11232, 15776, 17332, 44448, 31420, 10980, 20272, 8350, 25824, 7750, 23360, 8684, 27594, 36657, 8654, 42305, 35080, 6898, 8452, 9983, 12610, 13407, 11716, 45591, 11250, 20904, 17450, 10956, 15996, 16712, 12570, 15860, 18450, 20745, 13650, 11219, 11298, 31752, 8240, 29112, 17626, 28845, 13410, 17820, 13150, 8872, 17590, 9876, 6657, 22588, 11097, 16925, 12737, 13320, 23164, 35216, 10367, 19175, 11155, 18996, 9630, 10428, 14076, 16768, 12719, 10664, 9062, 5004, 12136, 6966, 7556, 42980, 15652, 4706, 7209, 8728, 10762, 8910, 6490, 5958, 18600, 16168, 17320, 8440, 8502, 8530, 8971, 10800, 15560, 14688, 19290, 9705, 29980, 9268, 16343, 17888, 8970, 30284, 14410, 19442, 9662, 11352, 15372, 12906, 13839, 50864, 7797, 14945, 24750, 12880, 19309, 18320, 13677, 15550, 14583, 7954, 11325, 11663, 6950, 12420, 7872, 36080, 8997, 7328, 7243, 13000, 17333, 11498, 11700, 9549, 10357, 6996, 16300, 17964, 10230, 7806, 4055, 10068, 10438, 9712, 10532, 12000, 7732, 10764, 10085, 8360, 6078, 10950, 12204, 5970, 6702, 11400, 11887, 9076, 7575, 8298, 7852, 8662, 8369, 9332, 9450, 51010, 8666, 8460, 7670, 25150, 14648, 9106, 9540, 8310, 52210, 15900, 8514, 13256, 8478, 12167, 8370, 14166, 10530, 11650, 22420, 34380, 27306, 49886, 48595, 10238, 13736, 42830, 14793, 5742, 14679, 15613, 17218, 22913, 7191, 20718, 29835, 15399, 32385, 24120, 25404, 5364, 25818, 12232, 13732, 27666, 16355, 13712, 13486, 19266, 21794, 16764, 12022, 10391, 16338, 13219, 11020, 7217, 16503, 14235, 12778, 9630, 8550, 8532, 7854, 17735, 8820, 8256, 8100, 24600, 14436, 7662, 7404, 6546, 10080, 6418, 7261, 7744, 6878, 10806, 7780, 7659, 8700, 8670, 7384, 8622, 7596, 12978, 16332, 9405, 6893, 8025, 15520, 19896, 7408, 5554, 49280, 12690, 8500, 5893, 10335, 4803, 6090, 8810, 14038, 4731, 5500, 5287, 17175, 13735, 18810, 9738, 9860, 17120, 15858, 22434, 18910, 16070, 15678, 12140, 16472, 24856, 12140, 21814, 17676, 22689, 18633, 19536, 34514, 13900, 12024, 12384, 6017, 6016, 9306, 4941, 14376, 4650, 38958, 33487, 15034, 29936, 27250, 45554, 29585, 10438, 10562, 10560, 16850, 16484, 32651, 23290, 19606, 27198, 13826, 30176, 18045, 14040, 15776, 20120, 13660, 13230, 42886, 42368, 21970, 10700, 29680, 13782, 42078, 12290, 13194, 15196, 16533, 16110, 16228, 12694, 12921, 13347, 12566, 11581, 12154, 11933, 11385, 11350, 35874, 17200, 18033, 20000, 7721, 11875, 7288, 12654, 5533, 7772, 9900, 13875, 7447, 11606, 7278, 7753, 7124, 10572, 7043, 5924, 11520, 11730, 38010, 9450, 7192, 12820, 8240, 8643, 6532, 9136, 5713, 12697, 9397, 11250, 42610, 14468, 9679, 16070, 15085, 16008, 11090, 12267, 10620, 10260, 13528, 8964, 11325, 11070, 12425, 9510, 12600, 14721, 18812, 19236, 12070, 13474, 10920, 8902, 11175, 23440, 6794, 4572, 7735, 15804, 8169, 4770, 6426, 22720, 12196, 15504, 15180, 13801, 16243, 30634, 14565, 17496, 16002, 19560, 13403, 14165, 11610, 15508, 16391, 16722, 16688, 7962, 33024, 22212, 16430, 17920, 11934, 12222, 13522, 14515, 23590, 44350, 25560, 11420, 10715, 12060, 20912, 35604, 16848, 12240, 25550, 11402, 13272, 14976, 15363, 16676, 18017, 15840, 13991, 25100, 24096, 13260, 26832, 11826, 8880, 13362, 9280, 8242, 3790, 15075, 12984, 9682, 7650, 12798, 13440, 14612, 6840, 8558, 9773, 20890, 8780, 22860, 5700, 18576, 9371, 9024, 11446, 18986, 10463, 9234, 9876, 12834, 9896, 9420, 10371, 6426, 6890, 19890, 6395, 31500, 12590, 6300, 16208, 30200, 5059, 5776, 18966, 8434, 7768, 6990, 8938, 17505, 8006, 5717, 20115, 16390, 5878, 7183, 16206, 7144, 36252, 25242, 21258, 7323, 16250, 46560, 11310, 6427, 7968, 6109, 5369, 8904, 8819, 11300, 12418, 5623, 6376, 26688, 7101, 6718, 7525, 6886, 11800, 6349, 6680, 8036, 6277, 7822, 7527, 8589, 13594, 14436, 19249, 17012, 14258, 13226, 13775, 13724, 10811, 10752, 8430, 8912, 9618, 17100, 11480, 21494, 14532, 13143, 17680, 13914, 11794, 16881, 18402, 25481, 13800, 20118, 12753, 16266, 10503, 11952, 7504, 9000, 10876, 12015, 10539, 10290, 16164, 10305, 4860, 19350, 7936, 8911, 8762, 11789, 8706, 9036, 5673, 3552, 3552, 3552, 10002, 10992, 11460, 8649, 12380, 7645, 6790, 8961, 7813, 9000, 6834
#> $ tuitfee_grad_nres <dbl> 17496, 17294, 13090, 22338, 26950, 28840, 10380, 21232, 12422, 19140, 15094, 18960, 12110, 24176, 32135, 18294, 19004, 19813, 10544, 10890, 10475, 16178, 13152, 8370, 16444, 12140, 17650, 19269, 17051, 16922, 16804, 17261, 17234, 16617, 16507, 16754, 16758, 16654, 16577, 16781, 17094, 28339, 28166, 27785, 28440, 28187, 27266, 8150, 17022, 14980, 17635, 18032, 17403, 13500, 13818, 10587, 11232, 15776, 17332, 44448, 31420, 10980, 20272, 17278, 25824, 16678, 23360, 17612, 27594, 36657, 17582, 42305, 35080, 12820, 24112, 20153, 30430, 13407, 25692, 45591, 11250, 20904, 17450, 23756, 37032, 16712, 12570, 15860, 18450, 20745, 13650, 24019, 24098, 31752, 8240, 29112, 17626, 28845, 13410, 17820, 13150, 28657, 17590, 24669, 18446, 22588, 24202, 16925, 30130, 13320, 23164, 35216, 21933, 19175, 11155, 18996, 9630, 21126, 14076, 16768, 12719, 10664, 24894, 15192, 12136, 14961, 13802, 42980, 30072, 14624, 20508, 28610, 26360, 8910, 17866, 17460, 18600, 37648, 17320, 22890, 22583, 23338, 8971, 10800, 15560, 14688, 19290, 19425, 29980, 16636, 25297, 17888, 16542, 30284, 14410, 19442, 9662, 11352, 15372, 12906, 22407, 50864, 14205, 14945, 24750, 12880, 19309, 18320, 13677, 15550, 30369, 12938, 15209, 11663, 6950, 12420, 7872, 36080, 17191, 14186, 16256, 13000, 17333, 11498, 11700, 22861, 27961, 6996, 16300, 17964, 10230, 20298, 10333, 10068, 23134, 9712, 22690, 12000, 17816, 10764, 10085, 16896, 13609, 10950, 12204, 5970, 6702, 16320, 28822, 21961, 18650, 21737, 18783, 20762, 20846, 19332, 23178, 51010, 25640, 8460, 19298, 25150, 20570, 14308, 11556, 8310, 52210, 15900, 12132, 26810, 15264, 12167, 13572, 14166, 10530, 11650, 22420, 34380, 27306, 49886, 48595, 10238, 13736, 42830, 14793, 5742, 26228, 31733, 33268, 22913, 8811, 20718, 29835, 27473, 32385, 24120, 25404, 5364, 25818, 18216, 13732, 27666, 29075, 13712, 13486, 19266, 43674, 32940, 20720, 15354, 24648, 24867, 11020, 7217, 33696, 29118, 12778, 9630, 8550, 8532, 15039, 26615, 8820, 12084, 8100, 24600, 14436, 7662, 10804, 6546, 10080, 6418, 17614, 22012, 6878, 10806, 20900, 16529, 8700, 8670, 14067, 8622, 7596, 12978, 16332, 9405, 11445, 8025, 15520, 19896, 12868, 10234, 49280, 12690, 8500, 20554, 10335, 8403, 14428, 22088, 14038, 8331, 19410, 19197, 17175, 13735, 18810, 11124, 9860, 17120, 15858, 22434, 18910, 16070, 15678, 19910, 21147, 24856, 17513, 30898, 17676, 22689, 30225, 19536, 34514, 19663, 12024, 19242, 11963, 9150, 24169, 15107, 14376, 10354, 38958, 33487, 15034, 29936, 27250, 45554, 29585, 19028, 19152, 19150, 16850, 16484, 32651, 23290, 19606, 27198, 13826, 30176, 18045, 14040, 15776, 20120, 13660, 13230, 42886, 42368, 21970, 10700, 29680, 13782, 42078, 12290, 13194, 15196, 16533, 16110, 16228, 24034, 24261, 24687, 23906, 22921, 23494, 23273, 22725, 22690, 35874, 17200, 18033, 20000, 20890, 11875, 20179, 12654, 16381, 7772, 9900, 13875, 19852, 28817, 20449, 21202, 19824, 25094, 19262, 16181, 11520, 11730, 38010, 9450, 17599, 12820, 8240, 20642, 15835, 14642, 5713, 12697, 15049, 11250, 42610, 26210, 16411, 16070, 15085, 16008, 19362, 12267, 10620, 10260, 30242, 8964, 11325, 11070, 32873, 17502, 12600, 25057, 18812, 19236, 12070, 22890, 10920, 13402, 11175, 23440, 15761, 9486, 22503, 15804, 22272, 10980, 12762, 22720, 14788, 15504, 15180, 23450, 26611, 30634, 22053, 17496, 19602, 19560, 13403, 20261, 11610, 22519, 16391, 16722, 24275, 7962, 33024, 22212, 16430, 17920, 11934, 12222, 13522, 21225, 23590, 44350, 25560, 19088, 10715, 12060, 35214, 35604, 16848, 12240, 25550, 11402, 13272, 21072, 22330, 22526, 18017, 15840, 20015, 25100, 24096, 13260, 26832, 11826, 8880, 25772, 9280, 8242, 3790, 15075, 32958, 19280, 7650, 27408, 24264, 27870, 6840, 15491, 23753, 20890, 8780, 22860, 5700, 18576, 23627, 9024, 11446, 18986, 19247, 23346, 25994, 31252, 15656, 21060, 24891, 6426, 6890, 19890, 13740, 31500, 12590, 14073, 16208, 30200, 13004, 13120, 18966, 17056, 14212, 14334, 18082, 17505, 15350, 13490, 20115, 16390, 7048, 14527, 16206, 15172, 36252, 25242, 21258, 14667, 16250, 46560, 11310, 13771, 16128, 13452, 12713, 19073, 17316, 21518, 24150, 13452, 13774, 26688, 22700, 13910, 14869, 14231, 11800, 7028, 6680, 23617, 19586, 18348, 23902, 17073, 13594, 14436, 19249, 40076, 30500, 13226, 13775, 32402, 10811, 28296, 8430, 8912, 18492, 17100, 28860, 21494, 27764, 25271, 28504, 13914, 26279, 16881, 18402, 25481, 13800, 20118, 26185, 28314, 20787, 11952, 16060, 23238, 10876, 12015, 10539, 10290, 16164, 10305, 4860, 19350, 7936, 18042, 17893, 24826, 17837, 18167, 14313, 3552, 3552, 3552, 28804, 10992, 11460, 17577, 12380, 16573, 6790, 31216, 16741, 9000, 19234
#> $ coa_grad_res <dbl> 22886, 25356, 25790, 25211, 28836, 30458, 24880, 23756, 18408, 35488, 20119, 27551, 32550, 26533, 29683, 24739, 25618, 23832, 21167, 24768, 19606, 26548, 19302, 21394, 34888, 30458, 36191, 27342, 26725, 22910, 26095, 25287, 23936, 25211, 24521, 26530, 25920, 25468, 26353, 22993, 25108, 29109, 30027, 30126, 29379, 30378, 45134, 26590, 28066, 34366, 37365, 37616, 25217, 32041, 32637, 30167, 27624, 35450, 35860, 62889, 49750, 29420, 38695, 25514, 44274, 26498, 42750, 27390, 46035, 53174, 27250, 59733, 53530, 21154, 26650, 26783, 28492, 24917, 23969, 61446, 26016, 40945, 37678, 26430, 31932, 33452, 28334, 31088, 35600, 35557, 28044, 26289, 27402, 46120, 17840, 46531, 37766, 44520, 28550, 38420, 31341, 24758, 34274, 26963, 25059, 40398, 29878, 30475, 27607, 34904, 40980, 55698, 25335, 47810, 26639, 37946, 25582, 25428, 37371, 33294, 20219, 22294, 21716, 20784, 27620, 22438, 22316, 60106, 33352, 19822, 27162, 25382, 23752, 21740, 21942, 20502, 34923, 33049, 38102, 22644, 23703, 21938, 21961, 19178, 29010, 23438, 36145, 21468, 40480, 28036, 32253, 33888, 23532, 41784, 25414, 33742, 21412, 33942, 31398, 24986, 28599, 70505, 23274, 29605, 36840, 25730, 36809, 37669, 25797, 27062, 28810, 20773, 25375, 21663, 13750, 28917, 20072, 50654, 23139, 20502, 19415, 24082, 28933, 23218, 25500, 21330, 23315, 20150, 32894, 30516, 24280, 20668, 16681, 23580, 24198, 25057, 22910, 27493, 20009, 21172, 23722, 23193, 22422, 28994, 23054, 19420, 23002, 23420, 34239, 21727, 21787, 22510, 22138, 22874, 22577, 24257, 23662, 67114, 22030, 19560, 21850, 35050, 34598, 26020, 20646, 23850, 64729, 26690, 29794, 32354, 26899, 23267, 23722, 23286, 19542, 26110, 29420, 51970, 40456, 67706, 62425, 26038, 25936, 53130, 27246, 15322, 22951, 29910, 30174, 40763, 22103, 39048, 44725, 28671, 51542, 38390, 41014, 15332, 41782, 21516, 24412, 43508, 27333, 29306, 26186, 35074, 36168, 29992, 24750, 24007, 27818, 27000, 23616, 19043, 32587, 27110, 33836, 22280, 21050, 20106, 27150, 30312, 17540, 20386, 19490, 37046, 26796, 19704, 20124, 24170, 22880, 18992, 20761, 23606, 20072, 25778, 23582, 22429, 23985, 22182, 19134, 19312, 17852, 28314, 30832, 20535, 18426, 19471, 31346, 35184, 20900, 18976, 69264, 31310, 14950, 19876, 24735, 18391, 19448, 23466, 26694, 15733, 21670, 21645, 33675, 28685, 37730, 23028, 26972, 36520, 32073, 37095, 34990, 33902, 30434, 30286, 32379, 38983, 29980, 40114, 36376, 35819, 40930, 30936, 51114, 31422, 19767, 30184, 18961, 20136, 25012, 18947, 31026, 19420, 56906, 48933, 25534, 43690, 40946, 68824, 46245, 30817, 30941, 30939, 32620, 31634, 48335, 44701, 37356, 42388, 29496, 59676, 36255, 30715, 28744, 40830, 26860, 28895, 59485, 63016, 43084, 26990, 51712, 25554, 56604, 23765, 26857, 31212, 28033, 30350, 31355, 25730, 24643, 29289, 31702, 28932, 28554, 27723, 26797, 28398, 54196, 35509, 32277, 36395, 20087, 28235, 21453, 27649, 16429, 17072, 25510, 23779, 20220, 28670, 21797, 19989, 22927, 24731, 21375, 18933, 25720, 23702, 55214, 20624, 21959, 23824, 21104, 20921, 18868, 25630, 15853, 28283, 22643, 28748, 60008, 33736, 25949, 31500, 23350, 31258, 26592, 23073, 22430, 21460, 29212, 19014, 23325, 23724, 28235, 25514, 26300, 28743, 32736, 31436, 24244, 28882, 25650, 22627, 24101, 32040, 26712, 17706, 22485, 31378, 24596, 15074, 18966, 39782, 25506, 29102, 27250, 29776, 29521, 45186, 32555, 27690, 29952, 31912, 23603, 27417, 24510, 31382, 30277, 32264, 32430, 24090, 53369, 37572, 25955, 33486, 17984, 30172, 25992, 29947, 33090, 55050, 40315, 28068, 23415, 28876, 38770, 53480, 23298, 28138, 44550, 23970, 26684, 28938, 28597, 35946, 34510, 25840, 30571, 36948, 37214, 27420, 40332, 22435, 25070, 27933, 23430, 24002, 17840, 24140, 29017, 23636, 24056, 28472, 26712, 26076, 20355, 23207, 25572, 38370, 21092, 35276, 21230, 33306, 24113, 22140, 25676, 31516, 25543, 23182, 23976, 30336, 24810, 21750, 27421, 20046, 25550, 33800, 19291, 47950, 24208, 19523, 33128, 43100, 18028, 18894, 34473, 26102, 24616, 20364, 26813, 32915, 20856, 16655, 35133, 28310, 17070, 20519, 28578, 18355, 52852, 39864, 37204, 20839, 24550, 58660, 31066, 19941, 19958, 21137, 18947, 26146, 22947, 26342, 27988, 20627, 21682, 44438, 22325, 26082, 22226, 18529, 28706, 20785, 19440, 21936, 18737, 18192, 22373, 22841, 26908, 28186, 36369, 30514, 29015, 25491, 24575, 32018, 28111, 25226, 24521, 20802, 24828, 35264, 26319, 35584, 27442, 30347, 32454, 26562, 26815, 32461, 31162, 39339, 26900, 37287, 28611, 35277, 25428, 25557, 20330, 20860, 23416, 24564, 23125, 24970, 28644, 21815, 12930, 37358, 19946, 19999, 20062, 25925, 19856, 21836, 20233, 18052, 18052, 18052, 22462, 23564, 28180, 25907, 29829, 27359, 13990, 23233, 26517, 30982, 23762
#> $ coa_grad_nres <dbl> 31016, 35062, 25790, 37207, 45316, 48602, 24880, 34412, 24006, 35488, 27265, 36690, 32550, 39203, 49435, 33626, 35338, 35295, 25793, 29700, 24200, 26548, 19302, 23824, 34888, 30458, 36191, 36270, 35653, 31838, 35023, 34215, 32864, 34139, 33449, 35458, 34848, 34396, 35281, 31921, 34036, 44211, 45129, 45228, 44481, 45480, 45134, 26590, 28066, 34366, 37365, 37616, 34145, 32041, 32637, 30167, 27624, 35450, 35860, 62889, 49750, 29420, 38695, 34442, 44274, 35426, 42750, 36318, 46035, 53174, 36178, 59733, 53530, 27076, 42310, 36953, 46312, 24917, 37945, 61446, 26016, 40945, 37678, 39230, 52968, 33452, 28334, 31088, 35600, 35557, 28044, 39089, 40202, 46120, 17840, 46531, 37766, 44520, 28550, 38420, 31341, 44543, 34274, 41756, 36848, 40398, 42983, 30475, 45000, 34904, 40980, 55698, 36901, 47810, 26639, 37946, 25582, 36126, 37371, 33294, 20219, 22294, 37548, 30972, 27620, 30433, 28562, 60106, 47772, 29740, 40461, 45264, 39350, 21740, 33318, 32004, 34923, 54529, 38102, 37094, 37784, 36746, 21961, 19178, 29010, 23438, 36145, 31188, 40480, 35404, 41207, 33888, 31104, 41784, 25414, 33742, 21412, 33942, 31398, 24986, 37167, 70505, 29682, 29605, 36840, 25730, 36809, 37669, 25797, 27062, 44596, 25757, 29259, 21663, 13750, 28917, 20072, 50654, 31333, 27360, 28428, 24082, 28933, 23218, 25500, 34642, 40919, 20150, 32894, 30516, 24280, 33160, 22959, 23580, 36894, 25057, 35068, 27493, 30093, 21172, 23722, 31729, 29953, 28994, 23054, 19420, 23002, 28340, 51174, 34612, 32862, 35949, 33069, 34974, 35054, 34257, 37390, 67114, 39004, 19560, 33478, 35050, 40520, 31222, 22662, 23850, 64729, 26690, 33412, 45908, 33685, 23267, 28924, 23286, 19542, 26110, 29420, 51970, 40456, 67706, 62425, 26038, 25936, 53130, 27246, 15322, 34500, 46030, 46224, 40763, 23723, 39048, 44725, 40745, 51542, 38390, 41014, 15332, 41782, 27500, 24412, 43508, 40053, 29306, 26186, 35074, 58048, 46168, 33448, 28970, 36128, 38648, 23616, 19043, 49780, 41993, 33836, 22280, 21050, 20106, 34335, 39192, 17540, 24214, 19490, 37046, 26796, 19704, 23524, 24170, 22880, 18992, 31114, 37874, 20072, 25778, 36702, 31299, 23985, 22182, 25817, 19312, 17852, 28314, 30832, 20535, 22978, 19471, 31346, 35184, 26360, 23656, 69264, 31310, 14950, 34537, 24735, 21991, 27786, 36744, 26694, 19333, 35580, 35555, 33675, 28685, 37730, 24414, 26972, 36520, 32073, 37095, 34990, 33902, 30434, 38056, 37054, 38983, 35353, 49198, 36376, 35819, 52522, 30936, 51114, 37185, 19767, 37042, 24907, 23270, 39875, 29113, 31026, 25124, 56906, 48933, 25534, 43690, 40946, 68824, 46245, 39407, 39531, 39529, 32620, 31634, 48335, 44701, 37356, 42388, 29496, 59676, 36255, 30715, 28744, 40830, 26860, 28895, 59485, 63016, 43084, 26990, 51712, 25554, 56604, 23765, 26857, 31212, 28033, 30350, 31355, 37070, 35983, 40629, 43042, 40272, 39894, 39063, 38137, 39738, 54196, 35509, 32277, 36395, 33256, 28235, 34344, 27649, 27277, 17072, 25510, 23779, 32625, 45881, 34968, 33438, 35627, 39253, 33594, 29190, 25720, 23702, 55214, 20624, 32366, 23824, 21104, 32920, 28171, 31136, 15853, 28283, 28295, 28748, 60008, 45478, 32681, 31500, 23350, 31258, 34864, 23073, 22430, 21460, 45926, 19014, 23325, 23724, 48683, 33506, 26300, 39079, 32736, 31436, 24244, 38298, 25650, 27127, 24101, 32040, 35679, 22620, 37253, 31378, 38699, 21284, 25302, 39782, 28098, 29102, 27250, 39425, 39889, 45186, 40043, 27690, 33552, 31912, 23603, 33513, 24510, 38393, 30277, 32264, 40017, 24090, 53369, 37572, 25955, 33486, 17984, 30172, 25992, 36657, 33090, 55050, 40315, 35736, 23415, 28876, 53072, 53480, 23298, 28138, 44550, 23970, 26684, 35034, 35564, 41796, 34510, 25840, 36595, 36948, 37214, 27420, 40332, 22435, 25070, 40343, 23430, 24002, 17840, 24140, 48991, 33234, 24056, 43082, 37536, 39334, 20355, 30140, 39552, 38370, 21092, 35276, 21230, 33306, 38369, 22140, 25676, 31516, 34327, 37294, 40094, 48754, 30570, 33390, 41941, 20046, 25550, 33800, 26636, 47950, 24208, 27296, 33128, 43100, 25973, 26238, 34473, 34724, 31060, 27708, 35957, 32915, 28200, 24428, 35133, 28310, 18240, 27863, 28578, 26383, 52852, 39864, 37204, 28183, 24550, 58660, 31066, 27285, 28118, 28480, 26291, 36315, 31444, 36560, 39720, 28456, 29080, 44438, 37924, 33274, 29570, 25874, 28706, 21464, 19440, 37517, 32046, 28718, 38748, 31325, 26908, 28186, 36369, 53578, 45257, 25491, 24575, 50696, 28111, 42770, 24521, 20802, 33702, 35264, 43699, 35584, 40674, 42475, 43278, 26562, 41300, 32461, 31162, 39339, 26900, 37287, 42043, 47325, 35712, 25557, 28886, 35098, 23416, 24564, 23125, 24970, 28644, 21815, 12930, 37358, 19946, 29130, 29193, 38962, 28987, 30967, 28873, 18052, 18052, 18052, 41264, 23564, 28180, 34835, 29829, 36287, 13990, 45488, 35445, 30982, 36162
# create version of data frame df_mba that turns class=labelled variables to factor variables
df_mba_fac <- as_factor(df_mba, only_labelled = TRUE)
# save as RDS
#save(df_mba_fac, file = "../../data/college_scorecard/output_data/df_debt_earn_mba.Rdata")
##########
########## ELS:2002 data
##########
# RUN SCRIPT THAT CREATES STUDENT-LEVEL DATA FRAME CONTAINING ALL VARIABLES AND CREATES DATA FRAME WITH A SUBSET OF VARIABLES
#NOTE: this script will take 30 seconds to a minute to run because loading a dataset w/ about 16,000 observations and 4,000 variables from a website
source(file = url('https://github.com/anyone-can-cook/educ152/raw/main/scripts/els/read_els_by_pets.R'))
#source(file = file.path('.','..','..','scripts','els','read_els_by_pets.R'))
#list.files(path = file.path('.','..','..','scripts','els'))
# Create a dataframe df_els_stu_fac that has categorical variables as factor class variables rather than labelled class variables
#df_els_stu_fac <- as_factor(df_els_stu, only_labelled = TRUE)
# convert continuous variables we know we want numeric back to numeric
#for (v in c('bytxmstd','bytxrstd','f1txmstd','f3stloanamt','f3stloanpay','f3ern2011','f3tzrectrans','f3tzreqtrans','f3tzschtotal')) {
# df_els_stu_fac[[v]] <- df_els_stu[[v]]
#}1.2 ELS:2002 data
The Educational Longitudinal Study (ELS) of 2002, referred to as ELS:2002
- Nationally representative, longitudinal survey of US 10th graders in 2002, followed them from 2002 to 2013
- Created by the National Center for Education Statistics, a branch of the U.S. Department of Education
- LINK to ELS:2002 website
- LINK to the NCES “Online Codebook” website, which contains “public-use” versions of ELS datasets and detailed information about all variables
- variables that could potentially be used to identify ELS survey respondents are “suppressed” from public-use datasets
- these variables are present in “restricted” versions of ELS datasets
ELS datasets we created
- student-level data frame
df_els_stu_allhas all variables (about 4,000) and all observations (about 16,200 observations); one observation for each student - student-level data frame
df_els_stuhas a subset of variables and a subset of observations- sample is respondents who filled completed all waves of the survey; who attended postsecondary education at some point by 2012; and some other minor sample criteria around observations not being missing for certain variables
- for both
df_els_stu_allanddf_els_stu, most categorical variables arelabelledclass variables - student-level data frame
df_els_stu_facis exact same asdf_els_stuexcept categorical variables arefactorclass; categorical variables must be factor class when running regression models
In the coming weeks, we want your help in identifying variables of interest and populations/samples of interest!
Investigate df_els_stu (output not shown)
Investigate df_els_stu_fac (output not shown)
Can use the lookfor() function from the labelled package to query which variables and variable labels contain certain words
- syntax (with defaults):
look_for(data, ..., labels = TRUE, ignore.case = TRUE, details = TRUE)- where argument
...contains “strings” (e.g., words) you are looking for, enclosed in quotation marks
- example syntax, looking for variable names and variable labels that contain the word “internship”
lookfor(data=df_els_stu_all, 'internship',labels = TRUE, ignore.case = TRUE, details = TRUE)
useful to use lookfor() to query the dataset df_els_stu_all because this dataset has so many variables (more than 4,000)
# query data frame df_els_stu_all
lookfor(data=df_els_stu_all, 'how far in school',labels = TRUE, ignore.case = TRUE, details = TRUE)
#> # A tibble: 14 x 13
#> pos variable label col_type class type levels value_labels na_values na_range unique_values n_na range
#> <int> <chr> <chr> <chr> <named list> <chr> <named list> <named list> <named list> <named list> <int> <int> <named list>
#> 1 59 bystexp How far in school student thinks will get-composite dbl+lbl <chr [3]> double <NULL> <dbl [10]> <NULL> <NULL> 10 0 <dbl+lbl [2]>
#> 2 60 byparasp How far in school parent wants 10th-grader to go-composite dbl+lbl <chr [3]> double <NULL> <dbl [8]> <NULL> <NULL> 8 0 <dbl+lbl [2]>
#> 3 219 f1stexp F1 how far in school student thinks will get-composite dbl+lbl <chr [3]> double <NULL> <dbl [11]> <NULL> <NULL> 11 0 <dbl+lbl [2]>
#> 4 1498 bys56 How far in school student thinks will get dbl+lbl <chr [3]> double <NULL> <dbl [12]> <NULL> <NULL> 12 0 <dbl+lbl [2]>
#> 5 1524 bys65a How far in school mother wants 10th-grader to go dbl+lbl <chr [3]> double <NULL> <dbl [13]> <NULL> <NULL> 13 0 <dbl+lbl [2]>
#> 6 1525 bys65b How far in school father wants 10th-grader to go dbl+lbl <chr [3]> double <NULL> <dbl [13]> <NULL> <NULL> 13 0 <dbl+lbl [2]>
#> 7 1799 f1s42 How far in school respondent thinks will get dbl+lbl <chr [3]> double <NULL> <dbl [13]> <NULL> <NULL> 13 0 <dbl+lbl [2]>
#> 8 1800 f1s43a How far in school mother wants respondent to go dbl+lbl <chr [3]> double <NULL> <dbl [15]> <NULL> <NULL> 15 0 <dbl+lbl [2]>
#> 9 1801 f1s43b How far in school father wants respondent to go dbl+lbl <chr [3]> double <NULL> <dbl [15]> <NULL> <NULL> 15 0 <dbl+lbl [2]>
#> 10 2059 f1d57 How far in school respondent thinks will get (DO) dbl+lbl <chr [3]> double <NULL> <dbl [13]> <NULL> <NULL> 13 0 <dbl+lbl [2]>
#> 11 2060 f1d58a How far in school mother wants respondent to go (DO) dbl+lbl <chr [3]> double <NULL> <dbl [15]> <NULL> <NULL> 15 0 <dbl+lbl [2]>
#> 12 2061 f1d58b How far in school father wants respondent to go (DO) dbl+lbl <chr [3]> double <NULL> <dbl [15]> <NULL> <NULL> 15 0 <dbl+lbl [2]>
#> 13 2980 byp79 How far in school wants 10th-grader to go dbl+lbl <chr [3]> double <NULL> <dbl [12]> <NULL> <NULL> 12 0 <dbl+lbl [2]>
#> 14 2996 byp81 How far in school parent expects 10th-grader will go dbl+lbl <chr [3]> double <NULL> <dbl [13]> <NULL> <NULL> 13 0 <dbl+lbl [2]>
# query data frame df_els_stu
lookfor(data=df_els_stu, 'debt',labels = TRUE, ignore.case = TRUE, details = TRUE)
#> # A tibble: 0 x 0
lookfor(data=df_els_stu, 'loan',labels = TRUE, ignore.case = TRUE, details = TRUE)
#> # A tibble: 4 x 13
#> pos variable label col_type class type levels value_labels na_values na_range unique_values n_na range
#> <int> <chr> <chr> <chr> <named list> <chr> <named list> <named list> <named list> <named list> <int> <int> <named list>
#> 1 85 f3stloanamt Total amount borrowed in student loans dbl+lbl <chr [3]> double <NULL> <dbl [3]> <NULL> <NULL> 58 0 <dbl+lbl [2]>
#> 2 86 f3stloanevr Whether R took out any student/PSE loans dbl+lbl <chr [3]> double <NULL> <dbl [6]> <NULL> <NULL> 2 0 <dbl+lbl [2]>
#> 3 87 f3stloanpay Amount currently paid monthly toward student loan balance dbl+lbl <chr [3]> double <NULL> <dbl [3]> <NULL> <NULL> 41 0 <dbl+lbl [2]>
#> 4 92 f3totloan total loans taken out to pay for postsecondary education as of f3 (2013) dbl <chr [1]> double <NULL> <NULL> <NULL> <NULL> 58 0 <dbl [2]>1.3 Example research questions
For the multivariate regression lecture, we will focus on using multivariate regression to answer causal research questions that follow the form “what is the effect of \(X\) on \(Y\)?”
We will answer one research question that uses experimental data from the Tennessee STAR Experiment and also research questions that use observational data from ELS:2002
- [experimental design] What is the effect of being in a small class size (\(X_i=1\)) vs. regular class size (\(X_i=0\)) on reading achievement score (\(Y_i\)) for kindergarten students?
- Using data from the Tennessee Student Teacher Achievement Ratio (STAR) experiment
- Kindergarten students randomly assigned to “small” [treatment] vs. “regular” [control] class size based on flip of a coin
- LINK to information and data on the Tennessee STAR project
- \(X\) var is
treatment; \(Y\) var isread
df_stark %>% group_by(treatment) %>% summarize(
mean_read = mean(read, na.rm = TRUE),
)
#> # A tibble: 2 x 2
#> treatment mean_read
#> <dbl> <dbl>
#> 1 0 435.
#> 2 1 441.- [observational design, categorical \(X\)] What is the effect of having an internship or co-op job (\(X\)) (in 2005-06) on 2011 earnings (\(Y\))? [for students who were enrolled in postsecondary education in 2005-06]
- \(Y\) is
f3ern2011 - \(X\) is
f2intern0506(this would be sophomore year for students who graduated HS in spring 2004 and immediately entered postsecondary education)f2intern0506==0: no co-op/internship
- sample:
f2enroll0506=='yes'
- \(Y\) is
df_els_stu_fac %>% filter(f2enroll0506=='yes') %>%
group_by(f2intern0506) %>% summarize(
mean_earn = mean(f3ern2011, na.rm = TRUE),
n_nonmissing = sum(!is.na(f3ern2011))
)
#> # A tibble: 3 x 3
#> f2intern0506 mean_earn n_nonmissing
#> <fct> <dbl> <int>
#> 1 no 28764. 6858
#> 2 yes 33863. 450
#> 3 <NA> 34000 11- [observational design, categorical \(X\)] What is the effect of field of study (\(X\)) on earnings (\(Y\))? [for respondents not currently enrolled in postsecondary education]
- answer the RQ separately for: certificate degrees; associate’s degrees; for bachelor’s degrees?
- \(Y\) is
f3ern2011 - for certificate degrees: \(X\) is
f3tzcrt1cip2 - for associate’s degrees: \(X\) is
f3tzasc1cip2 - for bachelor’s degrees: \(X\) is
f3tzbch1cip2
# certificate degrees
df_els_stu_fac %>% filter(!(f3tzcrt1cip2 %in% c('Missing','Item legitimate skip/NA')), f3a01d=='No') %>%
group_by(f3tzcrt1cip2) %>% summarize(
mean_earn = mean(f3ern2011, na.rm = TRUE),
n_nonmissing = sum(!is.na(f3ern2011))
)
#> # A tibble: 5 x 3
#> f3tzcrt1cip2 mean_earn n_nonmissing
#> <fct> <dbl> <int>
#> 1 Personal and culinary services 20797. 86
#> 2 Mechanic/repair technologies/technicians 31174. 53
#> 3 Health/related clinical sciences 20842. 241
#> 4 Business/management/marketing/related 29976. 21
#> 5 Other 31565. 108
# associates degreees
df_els_stu_fac %>% filter(!(f3tzasc1cip2 %in% c('Missing','Item legitimate skip/NA')), f3a01d=='No') %>%
group_by(f3tzasc1cip2) %>% summarize(
mean_earn = mean(f3ern2011, na.rm = TRUE),
n_nonmissing = sum(!is.na(f3ern2011))
)
#> # A tibble: 11 x 3
#> f3tzasc1cip2 mean_earn n_nonmissing
#> <fct> <dbl> <int>
#> 1 Computer/information science/support 29923. 26
#> 2 Personal and culinary services 26161. 31
#> 3 Education 16517. 30
#> 4 Engineering technologies/technicians 29593. 28
#> 5 Liberal arts/sci/gen studies/humanities 24622. 218
#> 6 Security and protective services 27756. 39
#> 7 Mechanic/repair technologies/technicians 38006. 35
#> 8 Visual and performing arts 19403. 31
#> 9 Health/related clinical sciences 29003. 151
#> 10 Business/management/marketing/related 33240. 107
#> 11 Other 28303. 88
# bachelor's degreees
df_els_stu_fac %>% filter(!(f3tzbch1cip2 %in% c('Missing','Item legitimate skip/NA')), f3a01d=='No') %>%
group_by(f3tzbch1cip2) %>% summarize(
mean_earn = mean(f3ern2011, na.rm = TRUE),
n_nonmissing = sum(!is.na(f3ern2011))
) %>% print(n=30)
#> # A tibble: 27 x 3
#> f3tzbch1cip2 mean_earn n_nonmissing
#> <fct> <dbl> <int>
#> 1 Agriculture/operations/related sciences 30788. 33
#> 2 Natural resources and conservation 27828. 29
#> 3 Architecture and related services 30478. 23
#> 4 Communication, journalism, related 31085. 240
#> 5 Computer/information science/support 44458. 60
#> 6 Education 29519. 185
#> 7 Engineering 51410. 156
#> 8 Engineering technologies/technicians 44267. 36
#> 9 Foreign languages/literature/linguistics 32247. 45
#> 10 Family/consumer sciences/human sciences 26189. 53
#> 11 English language and literature/letters 24202. 96
#> 12 Liberal arts/sci/gen studies/humanities 29733. 45
#> 13 Biological and biomedical sciences 20472. 137
#> 14 Mathematics and statistics 38931. 36
#> 15 Multi/interdisciplinary studies 25251. 66
#> 16 Parks/recreation/leisure/fitness studies 26736. 106
#> 17 Philosophy and religious studies 23977. 22
#> 18 Physical sciences 33311. 37
#> 19 Psychology 25680. 176
#> 20 Security and protective services 36736. 70
#> 21 Public administration/social service 26639. 61
#> 22 Social sciences 32916. 318
#> 23 Visual and performing arts 24297. 215
#> 24 Health/related clinical sciences 42889. 264
#> 25 Business/management/marketing/related 41515. 751
#> 26 History 25771. 75
#> 27 Other 29107. 61- [observational design, continuous \(X\)] What is the effect of amount borrowed in student loans (\(X\)) on earnings (\(Y\)) for respondents not currently enrolled in postsecondary education
- \(X\) var is
f3totloan; \(Y\) var isf3ern2011 - sample:
f3a01d=='No'
- \(X\) var is
df_els_stu_fac %>% filter(f3a01d=="No") %>% ggplot(aes(x=f3totloan, y=f3ern2011)) + geom_point() + stat_smooth(method = 'lm')
summary(lm(formula = f3ern2011 ~ f3totloan, data = df_els_stu %>% filter(f3a01d==0)))
#>
#> Call:
#> lm(formula = f3ern2011 ~ f3totloan, data = df_els_stu %>% filter(f3a01d ==
#> 0))
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -29971 -16577 -3769 10351 221273
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 29971.343400 358.117571 83.691 <0.0000000000000002 ***
#> f3totloan -0.015558 0.009277 -1.677 0.0936 .
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 25220 on 6601 degrees of freedom
#> Multiple R-squared: 0.0004259, Adjusted R-squared: 0.0002745
#> F-statistic: 2.813 on 1 and 6601 DF, p-value: 0.09356
Why are we using test scores and earnings as dependent variables?
- Ordinary Least Squares (OLS) multivariate regression assumes continuous dependent variable; regression models with categorical dependent variables are a bit more difficult to interpret
- But in later weeks, we may introduce the “linear probability model,” which will enable us to model dichotomous (two-category) dependent variables (e.g., 0/1 did student graduate)
2 Bias and efficiency
Recall that the fundamental goal of inferential statistics is to make statements about population parameters by using estimators to calculate point estimates from sample data
- Desirable properties of our point estimates (e.g. \(\hat{\beta}\) or \(\bar{Y}\))
- Efficient
- Unbiased
Efficiency (also called “precision”)
- Definition: how close your point estimate(s) is to the population parameter
- Standard Error: on average, how far away is a point estimate from one random sample from the value of the population parameter
- Therefore, an efficient point estimate is one with a low standard error (in other words, the sampling distribution of \(\beta_1\) has low variance or is “tight” around the population parameter)
- often, the easiest way to increase efficiency (decrease standard errors) is to increase sample size
Bias
- Bias: consistently overestimates or underestimates population parameter in repeated random samples
- There are many different types of bias!
- Sampling Bias:
- Estimate of population parameter is biased because you fail to take a random sample
- Example: goal is to estimate high school graduation rate; take a random sample of 10th graders and see if they graduate within three years.
- Omitted variable bias:
- Bias in estimate of \(\beta_1\) due to omitting necessary “control” variables in your regression model; we will discuss later in lecture
In the picture below:
- imagine that vertical red line is the value of the population parameter
- the blue curve represents the sampling distribution from an unbiased estimator, which is centered at the value of the population parameter
- the red dotted curve is the sampling distribution from a biased estimator (e.g., if you used sample mode as the estimator for population mean)
Picture of Bias and Efficiency (or “Precision”)
3 OLS Assumptions
OLS assumptions
- Conditional independence assumption
- (necessary to make this assumption if we are trying to estimate causal effects)
- (\(X_i\), \(Y_i\)), \(i=1, ...n\) are independently and identically distributed (i.i.d)
- Large outliers are unlikely
- Homoskedasticity
- If these assumptions hold:
- Then our OLS estimators, \(\hat{\beta_0}\), \(\hat{\beta_1}\)…\(\hat{\beta_k}\), have normal distributions in large samples
- And because they have normal distributions, we can use \(\hat{\beta_0}\), \(\hat{\beta_1}\)…\(\hat{\beta_k}\), to test hypothesess about the population parameters \(\beta_0\), \(\beta_1\)…\(\beta_k\)
- If these assumptions are violated:
- We produced inefficeint and biased estimates, \(\hat{\beta_0}\) and \(\hat{\beta_1}\), of the population parameters \(\beta_0\) and \(\beta_1\)
3.1 Assumption 2: i.i.d.
- (\(X_i\), \(Y_i\)), \(i=1, ...n\) are independently and identically distributed (i.i.d)
What does this assumption mean?
- This assumption is about sampling
- This assumption has two parts:
- (\(X_i\), \(Y_i\)), \(i=1, ...n\) are independently distributed
- (\(X_i\), \(Y_i\)), \(i=1, ...n\) are identically distributed
- We will explain each part separately
(\(X_i\), \(Y_i\)), \(i=1, ...n\) are independently distributed
- In words: Knowing that observation i takes on particular values for X and Y tells you nothing about the probability of the next observation taking on particular values for X and Y
- When is assumption of independently distributed violated?
- Longitudinal data: knowing a data point in one time period tells you something about a data point in another time period.
- Ex: Amount of $ student received via a Federal Pell Grant freshman year at UA probably tells you something about how much $ student received via a Federal Pell Grant sophmore year at UA. Why? because Pell status is not likely to dramatically change from one year to another!
- Hierarchical data:
- Ex: Students are nested within classrooms. Knowing the reading test score of one student in a classroom is probably correlated with reading test score for another student in the same classroom.
- Longitudinal data: knowing a data point in one time period tells you something about a data point in another time period.
- This assumption is violated for both the Tennessee STAR and the ELS:2002 datasets we are working with for this lecture
- Tennessee STAR: students are nested in classrooms
- if students \(i=1\) and \(i=2\) are in the same classroom and we know the outcome for student \(i=1\), then this information helps us predict outcome for student \(i=2\) because scores within classrooms are likely to be positively correlated
- ELS:2002 data
- the sampling design was to randomly pick high schools, and then randomly sample about
30students within each high school
- the sampling design was to randomly pick high schools, and then randomly sample about
- Tennessee STAR: students are nested in classrooms
- What happens if this assumption is violated?
- Our standard errors are incorrect, likely to be too small (downward biase)
- Since hypothesis testing about \(\hat{\beta}_1\) is \(\text{point_estimate}/SE(\text{point_estimate})\), standard errors that are smaller than they should be will cause us to reject \(H_0: \hat{\beta}_1=0\) when we should not
- For this course, you do not need to worry about this assumption
- How to overcome violations of this assumption:
- “cluster” your standard errors to account for nested structure of data (e.g., standard errors clustered at the high-school level)
- this approach calculates standard errors that are “robust” to violations of the assumption; that is, you can use these standard errors whether the assumption is violated or not
- You don’t need to take a separate course on “hierarchical linear regression”
- this approach tries to model the structure of residuals, rather than calculating standard errors that are robust to violations of the assumption
- modeling the structure of residuals makes assumptions about distribution of residuals; avoid making unnecessary assumptions whenever possible
- “cluster” your standard errors to account for nested structure of data (e.g., standard errors clustered at the high-school level)
(\(X_i\), \(Y_i\)), \(i=1, ...n\) are identically distributed
- Prior to choosing sample of observations for the population, the probability distribution (i.e., the likelihood that \(Y_i\) takes on certain values) is the same for all observations
- This is always true if you take a random sample!
- One randomly selected observation has the same probability of taking on a certain value of \(Y_i\) as another randomly selected observation
- When is the assumption of identically distributed violated?
- Sampling bias:
- Ex: You want to investigate probability of being tardy to college lectures and take a sample of students living on campus. Sampling bias: you did not include commuter students. If you were to randomly select a student living on campus, they are not likely to have the same probability of being tardy to lecture than a randomly selected commuter student.
- Sampling bias:
- This assumption was badly violated in datasets where modeled the relationship between cost of attendance (\(X\)) and institution-level student debt (\(Y\)) or institution-level student earnings (\(Y\))
- Department of education provided debt data and earnings data only for programs with high enrollment (to protect student anonymity)
- So we don’t have a random sample of degree programs; we only have degree programs from high-enrollment programs; these programs are likely not representative of the population
- Why is sampling bias bad?
- we our sample is not representative of the population, then point estimates of population parameters calculated from this sample is likely to be systematically wrong (biased)
- Don’t need to worry about violations of this part of the assumption for this class
3.2 Assumption 3: outliers
- Large outliers are unlikely
- Outliers: observations with values of \(X_i\) and \(Y_i\) that are outside the “usual” range of the data
- Outliers will affect your regression coefficients!
- Why? Because outliers will shift our OLS regression line!
- Outliers are more likely to substantively affect results if your sample size is small
In the below graph of the relationship between cost of attendance (\(X\)) and institution-level student debt (\(Y\)) for MA programs in social work, we may be concerned that the high value of debt for the USC observation might affect or results
df_socialwork %>% ggplot(aes(x=coa_grad_res, y=debt_all_stgp_eval_mean)) + geom_point() + stat_smooth(method = 'lm')
Stock and Watson have a very technical, mathematical definition of when this likely; but in practice this is about really investigating/knowing your data
In practice, if you do find outliers:
- Be sure the data is entered correctly and cleaned
- Ex: Survey data codes missing data as very unusual values (-99, -99, 99, 98)
- Sometimes outliers belong in the data!
- I avoid removing observations just because they have a high value; this introduces sampling bias
- If they belong; can use natural log of the variable [not covered in this class]
- Ex: All money variables are usually converted to their natural log in econometrics or education research (e.g., state appropriations, tuition revenue, household income)
- Be sure the data is entered correctly and cleaned
3.3 Assumption 4: homoskedasticity
There is “generally” a fourth OLS assumption, but Stock and Watson do not list it in our textbook
- I’ll tell you why after we understand what it generally assumes…
OLS Assumption #4: The distribution of the residuals has constant variance (homoscedasticity)
- Homoskedasticity
- The distribution (the variance!) of the residuals, \(u_i = Y_i - \hat{Y_i}\), is constant for all observations. That is, it does not change for different values of X
- Homo-skedasticity = “equal” or “same” variances
- Heteroskedasticity
- The distribution (the variance!) of the residuals, \(u_i = Y_i - \hat{Y_i}\), is not constant for all observations. That is, it does change/differs for different values of X
- Hetero-skedasticity = “unequal” or “different” variances
Homoskedasticity and Heteroskedasticity shown graphically
- Practical example: What is the effect of student-teacher ratio on test scores? [Stock and Watson Example]
In the below graph of the relationship between cost of attendance (\(X\)) and institution-level student debt (\(Y\)) for MA programs in business (MBA), we may be concerned that the high value of debt for the USC observation might affect or results
- the black dots represent the actual values values of student debt (\(Y_i\))
- Blue line represents predicted value of debt (\(\hat{Y}_i\)) for an institution with a particular value of cost of attendance (\(X_i\))
- The residual \(\hat{u}_i\) (\(\hat{u}_i = Y_i - \hat{Y}_i\)) represents how far off our prediction is for a particular observation \(i\)
- The “distribution” of the residual gets at how far off our predictions tend to be
- We could calculate this distribution separately for different values of \(X\)
- But visually, we can see that predicted value of debt (\(\hat{Y}_i\)) tend to be closer to actual values of debt \(Y_i\) for lower values of cost of attendance
- therefore, the distribution of residuals differs across values of \(X\)
- therefore, these residuals are heteroskedastic rather than homoskedastic
df_mba %>% ggplot(aes(x=coa_grad_res, y=debt_all_stgp_eval_mean)) + geom_point() + stat_smooth(method = 'lm')
- Why is homoskedasticity/heteroskedasticity important?
- Because our formula for calculating SE(\(\hat{\beta_1}\)) changes based on homoskedastic or heteroskedastic residuals!
- Our standard error measures how far our \(\hat{\beta_1}\) is likely to be from \(\beta_1\). In other words, it is used to calculate our t-value in hypothesis testing to determine statistical significance!
- In other statistics classes (non-econometrics), homoskedasticity is the fourth core assumption
- Stock and Watson only discuss the first three assumptions as core “OLS Assumptions”
- Why? Stock and Watson say:
- It is NEARLY IMPOSSIBLE to assume homoskedasticity; we almost always violate this assumption!
- But the solution to overcome this assumption is easy!
- We can just calculate heteroskedastic standard errors
- In other words, standard errors that are robust to violations of homoskedasticity
- Stock and Watson say:
- Rather than make homoskedasticity a core OLS Assumption and nearly always violate it;
- ALWAYS CALCULATE ROBUST STANDARD ERRORS AND DO NOT MAKE HOMOSKEDASTICITY A CORE OLS ASSUMPTION
- In this class, we won’t worry about calculating robust standard errors in R, but it’s not a very hard thing to do
code to calculate robust standard errors (not run)
4 Conditional independence assumption (CIA)
The conditional independence assumption (CIA) is (the most important) assumption we need to satisfy when we are trying to answer causal research questions of the type “what is the effect of \(X\) on \(Y\)?”
- The conditional independence assumption goes by many other names (e.g., “unconfoundedness”, “ignorability”, “exogenous selection”, etc.)
To explain the conditional independence assumption, we will go back and forth between the following two research questions (RQ):
- What is the effect of being in a having an internship (\(X_{1i}=1\)) vs. not having an internship e (\(X_{1i}=0\)) on subsequent earnings (\(Y_i\))?
- (we have observational data for this RQ)
- What is the effect of being in a small class size (\(X_{1i}=1\)) vs. regular class size (\(X_{1i}=0\)) on reading achievement score (\(Y_i\)) for kindergarten students?
- (we have experimental data for this RQ)
Population linear regression model
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ u_i\), where:
- \(Y_i\): is earnings for student \(i\) in 2011
- \(X_{1i}\): is whether student \(i\) had an internship in the 2005-06 academic year
- \(X_{1i}=0\): student \(i\) did not have an internship (“untreated” or “control”)
- \(X_{1i}=1\): student \(i\) had an internship (“treated”)
- \(u_i\) is all variables that affect \(Y_i\) but were not included in our model
- these are usually called “omitted variable”
- note that by definition an omitted variable is a variable that affects the outcome; doesn’t include variables that were excluded from model but do not affect the outcome
- let’s pretend that \(u_i\) consists of just one variable, parental income
- these are usually called “omitted variable”
Conditional independence assumption (CIA)
- CIA in words
- the independent variable \(X_i\) is unrelated to omitted variables, \(u_i\), not included in the model
- CIA mathematically
- \(E(u_i|X_i)=0\); the expected value of \(u_i\), given any value of \(X_i\), equals zero
- intuition:
- if we pretend that \(u_i\) consists of only one variable, the conditional independence assumption states that expected value of the omitted variable is equal to zero no matter the value of variable \(X_i\)
Conditional independence assumption (CIA) is always satisfied in a random assignment experiment
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ u_i\)
- In a random assignment experiment, students are randomly assigned to receive an internship (\(X_{1i}=1\)) or not (\(X_{1i}=0\))
- Because values of \(X_{1i}\) are randomly assigned, values of \(X_{1i}\) are by construction unrelated to other factors \(u_i\) (parental income) that affect \(Y_i\). so we have:
- \(E(u_i|X_i)=0\); or “independent variable \(X_i\) is unrelated to omitted variables, \(u_i\), not included in the model”
- we know that parental income \(u_i\) affects earnings \(Y_i\)
- students with rich parents have higher earnings than students with poor parents, because rich parents use connections to give their child job opportunities
- But we don’t have to be concerned that students with rich parents are more likely to get internships, because in an experiment internships are randomly assigned
Conditional independence assumption (CIA) is rarely satisfied when the treatment is not randomly assigned (self-selction into treatment
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ u_i\)
- we know that parental income \(u_i\) affects earnings \(Y_i\)
- why might parental income \(u_i\) be related to whether a student receives an internship or not \(X_{1i}\)?
- Some internships are unpaid or pay very little; only students with rich parents can afford to take an unpaid internship
- rich parents directly or indirectly help their child obtain an internship
- direct: parent asks professional contact to give internship to their child
- indirect: e.g., grew up in an affluent community; got an internship from a friend’s parent
Why does violation of Conditional independence assumption cause estimate of causal effects to be biased?
- Population linear model
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ u_i\)
- \(\beta_1\) is the “true” causal effect of having an internship (\(X\)) on earnings (\(Y\))
- OLS prediction line (our point estimates for the population parameters)
- \(Y_i = \hat{\beta_0} + \hat{\beta_1} X_{1i}\)
- \(\hat{\beta_1}\) is our estimate of the true causal effect of having an internship (\(X\)) on earnings (\(Y\))
- If parental income \(u_i\) (omitted from the model) positively affects \(Y\) and is positively related with receiving an internship (\(X\)) then:
- Our estimate \(\hat{\beta_1}\) is partly due to the relationship between income \(Y\) and internship \(X\) and partly due to the relationship between income \(Y\) and parental income \(u_i\)
- Therefore, \(\hat{\beta_1}\) is a biased point estimate of \(\beta_1\) (the “true” causal effect of internship on earnings) because it is picking up the relationship between income \(Y\) and parental income \(u_i\)
In the ELS:2002 dataset df_els_stu_fac, students self-select into having an internship or co-op job.
Let’s run a regression model of the relationship between internship (\(X\)), measured by f2intern0506, and 2011 earnings (\(Y\)), measured by f3ern2011
- our sample is the subset of students who were enrolled in 2005-06 (
f2enroll0506=='yes') because the variablef2intern0506was defined for these students
intern_mod1 <- lm(formula = f3ern2011 ~ f2intern0506, data = df_els_stu_fac %>% filter(f2enroll0506=='yes'))
summary(intern_mod1)
#>
#> Call:
#> lm(formula = f3ern2011 ~ f2intern0506, data = df_els_stu_fac %>%
#> filter(f2enroll0506 == "yes"))
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -33863 -16764 -3764 11236 221236
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 28763.9 296.7 96.937 < 0.0000000000000002 ***
#> f2intern0506yes 5099.2 1195.8 4.264 0.0000203 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 24570 on 7306 degrees of freedom
#> (11 observations deleted due to missingness)
#> Multiple R-squared: 0.002483, Adjusted R-squared: 0.002346
#> F-statistic: 18.18 on 1 and 7306 DF, p-value: 0.00002031
In above model, \(\hat{\beta_1}=\) 5,099
- We estimate that having an internship in 2005-06 as opposed to not having an internship is, on average, associated with a 5,099 dollar change in 2011 earnings
But we may concerned that parental income (measured by parent_income) : (a) has a positive relationship with earnings (\(Y\)) AND (b) is positively related with having an internship (\(X\))
- we’ll just assume parental income is positively related to having an internship
- graphically view relationship between parental income (X axis) and earnings (y axis)
df_els_stu_fac %>% filter(f2enroll0506=='yes') %>% ggplot(aes(x=parent_income, y=f3ern2011)) + geom_point() + stat_smooth(method = 'lm')
If we can include a measure of parental income in our model of the relationship between internship (\(X\)) and earnings (\(Y\)), then we no longer have to be concerned about whether the relationship between internship and parental income is biasing our results because we have “controlled” for this relationship
intern_mod2 <- lm(formula = f3ern2011 ~ f2intern0506+ parent_income, data = df_els_stu_fac %>% filter(f2enroll0506=='yes'))
summary(intern_mod2)
#>
#> Call:
#> lm(formula = f3ern2011 ~ f2intern0506 + parent_income, data = df_els_stu_fac %>%
#> filter(f2enroll0506 == "yes"))
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -42341 -16292 -2665 11335 224052
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 25112.008587 468.213580 53.63 < 0.0000000000000002 ***
#> f2intern0506yes 5286.486107 1187.848195 4.45 0.0000087 ***
#> parent_income 0.047771 0.004759 10.04 < 0.0000000000000002 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 24410 on 7305 degrees of freedom
#> (11 observations deleted due to missingness)
#> Multiple R-squared: 0.01605, Adjusted R-squared: 0.01579
#> F-statistic: 59.6 on 2 and 7305 DF, p-value: < 0.000000000000000225 Omitted Variable Bias
Population linear regression model
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ u_i\), where:
- \(Y_i\): is earnings for student \(i\) in 2011
- \(X_{1i}\): is whether student \(i\) had an internship in the 2005-06 academic year
- \(X_{1i}=0\): student \(i\) did not have an internship (“untreated” or “control”)
- \(X_{1i}=1\): student \(i\) had an internship (“treated”)
- \(u_i\) is all variables that affect \(Y_i\) but were not included in our model
We want to estimate \(\beta_1\), the “true” causal effect of X on Y
- Bias (general): when \(\hat{\beta_1}\) consistently underestimates \(\beta_1\) or overestimates \(\beta_1\)
- Omitted Variable Bias: bias in \(\hat{\beta_1}\) due to variables being omitted from the model
For omitted variable bias to occur, the omitted variable “Z” must satisfy two conditions:
- Z affects value of Y (i.e. Z is part of \(u_i\))
- and Z has a relationship with \(X\)
Omitted variable bias is caused by violations of the conditional expectations assumption (CIA):
- Recall the conditional independence assumption
- in words: the independent variable \(X_{1i}\) is unrelated to omitted variables, \(u_i\), not included in the model
- Omitted variable bias is caused by omitting a variable from your model that is related (e.g., correlated) to \(X_i\) (and that also affects \(Y_i\))
Omitted variable bias is not a concern in a random assignment experiment:
- If values of your independent variable of interest \(X_{1i}\) are randomly asssigned, then the value of \(X\) cannot have a systematic relationship with other variables that affect \(Y\) that have been omitted from your model
let’s consider Tenessee STAR experiment, where we are interested in the effect of class size (\(X\)) on reading achievement score (\(Y_i\))
- values of class size are randomly assigned: small class size (\(X_{1i}=1\)) vs. regular class size (\(X_{1i}=0\))
- below shows a regression of
treatment(\(X\)) andread(\(Y\))
summary(lm(formula = read ~ as.factor(treatment), data = df_stark))
#>
#> Call:
#> lm(formula = read ~ as.factor(treatment), data = df_stark)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -119.732 -21.732 -3.732 16.268 192.268
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 434.7323 0.7071 614.798 < 0.0000000000000002 ***
#> as.factor(treatment)1 5.8151 1.0377 5.604 0.0000000225 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 31.67 on 3743 degrees of freedom
#> Multiple R-squared: 0.00832, Adjusted R-squared: 0.008055
#> F-statistic: 31.4 on 1 and 3743 DF, p-value: 0.00000002246- The variable
lunch(free-reduced lunch), a proxy for household income, also affects reading achievement
summary(lm(formula = read ~ as.factor(lunch), data = df_stark))
#>
#> Call:
#> lm(formula = read ~ as.factor(lunch), data = df_stark)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -113.524 -20.524 -3.524 15.564 181.564
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 445.4356 0.6923 643.45 <0.0000000000000002 ***
#> as.factor(lunch)2 -16.9116 1.0055 -16.82 <0.0000000000000002 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 30.69 on 3734 degrees of freedom
#> (9 observations deleted due to missingness)
#> Multiple R-squared: 0.07043, Adjusted R-squared: 0.07018
#> F-statistic: 282.9 on 1 and 3734 DF, p-value: < 0.00000000000000022- But we are not concerned about omitted variable bias due to excluding
lunchfrom our model, because values of the class size treatment were randomly assigned
# model without controlling for lunch
summary(lm(formula = read ~ as.factor(treatment), data = df_stark))
#>
#> Call:
#> lm(formula = read ~ as.factor(treatment), data = df_stark)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -119.732 -21.732 -3.732 16.268 192.268
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 434.7323 0.7071 614.798 < 0.0000000000000002 ***
#> as.factor(treatment)1 5.8151 1.0377 5.604 0.0000000225 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 31.67 on 3743 degrees of freedom
#> Multiple R-squared: 0.00832, Adjusted R-squared: 0.008055
#> F-statistic: 31.4 on 1 and 3743 DF, p-value: 0.00000002246
# model with controlling for lunch
summary(lm(formula = read ~ as.factor(treatment) + as.factor(lunch), data = df_stark))
#>
#> Call:
#> lm(formula = read ~ as.factor(treatment) + as.factor(lunch),
#> data = df_stark)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -110.81 -20.71 -3.69 15.33 184.29
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 442.7119 0.8321 532.056 < 0.0000000000000002 ***
#> as.factor(treatment)1 5.8558 1.0023 5.843 0.00000000558 ***
#> as.factor(lunch)2 -16.8992 1.0010 -16.882 < 0.0000000000000002 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 30.55 on 3733 degrees of freedom
#> (9 observations deleted due to missingness)
#> Multiple R-squared: 0.07885, Adjusted R-squared: 0.07836
#> F-statistic: 159.8 on 2 and 3733 DF, p-value: < 0.00000000000000022What if values of “class size” were not randomly assigned?
- \(Y_i = \beta_0 + \beta_1X_i + u_i\)
- Y= average class reading test score
- X= class size
- Z= % of ELL students (omitted from model)
- For omitted variable bias to occur, the omitted variable “Z” must satisfy two conditions:
- Z affects value of Y (i.e. Z is part of \(u_i\));
- and Z has a relationship with \(X\)
- How does % of ELL students satisfy criteria of omitted variable bias?
- % of ELL affects value of average reading test scores (ELL students are likley to score at lower reading levels than native english speakers);
- and % of ELL students has a relationship with class size (policy: greater proportion of ELL students require smaller class sizes)
- Would omitting Z = “time of test administered” result in omitted variable bias?
- Would omitting Z = “teacher’s years of experience” result in omitted variable bias?
How to check for omitted variable bias
- Does Z affect Y?
- Ask yourself if it is plausible that omitted variable Z affects Y
- Does Z have a relationship with X?
- Ask yourself if it is plausible that omitted variable Z has some relationship with X
- Logical argument or diagnostic tests (e.g.,
df %>% summarise(cor(X, Z, use = "complete.obs")))
- In practice, diagnostic tests not used as much as logical arguments/literature review
- Correlation only picks up linear relationships, omitted variable bias includes non-linear relationships
- Relationship between X and Z is about “conditional relationship,” after controlling for other covariates
- Sometimes you don’t have a good measure of omitted variable Z
5.1 Independent variables for causal effects
Research questions that work and don’t work
- Fundamental requirements:
- Must be feasible for your independent variable to be randomly assigned in a random experiment
- Your dependent variable (Y) needs to be continuous or 0/1
- Your dependent variable (Y) must be measured at a time after your independent variable (X) occurs
Easiest independent variables that meet this requirement: participation in a program/intervention
- Federal programs: TRIO, Head Start
- Interventions: dropout prevention program, college prep, financial literary programs, using “services” like Think Tank, Cultural Centers, etc.
- Others: Student Teacher Ratio, type of sanction (diversion vs community service)
Avoid:
- Independent variables that can’t be randomly assigned or are hard to measure
- Attitudes or ideologies
- Culture
- Leadership Style
- Personal demographics
Exception to using personal demographics as X
Generally OK to use personal demographics as X when Y variable is determined by someone else
- Effect of racial identity (X) on the probability of receiving a reply to an admissions inquiry (Y)?
- Effect of racial identity (X) on probability of receiving a call back job interview (Y)?
- Effect of gender (X) on teacher course evaluations (Y)?
But these types of questions require really strong control variables!
6 Intro multivariate regression
6.1 Multivariate regression model
Population Regression Model
- Same as in “simple” (bivariate) regression; we just add more regressors (i.e., independent/control variables) into our model!
Population Regression Model
- \(Y_i = \beta_0 + \beta_1X_{1i} + \beta_2X_{2i} +\) … \(\beta_kX_{ki} + u_i\)
- Where:
- \(Y_i\) = observation i of dependent variable
- \(X_{1i}\) = observation i of the first regressor, \(X_1\)
- \(X_{2i}\) = observation i of the second regressor, \(X_2\)
- \(X_{ki}\) = observation i of the Kth regressor, \(X_k\)
- \(\beta_1\) = population average effect of Y for “change” in \(X_1\)
- if \(X_1\) is continuous: average effect of Y for one-unit increase/decrease in \(X_1\)
- if \(X_1\) is categorical: population average effect of being in the non-reference group as opposed to the reference group
- \(\beta_2\) = population average effect of Y for “change” in \(X_2\)
- \(\beta_k\) = population average effect of Y for “change” \(X_k\)
- \(\beta_0\) = average value of Y when the value of all independent variables (\(X_1, X_2 ...X_k\)) are equal to zero
- \(u_i\) = all other variables that affect the value of \(Y_i\) but are not included in the model
Writing out the population linear regression model
- Important to define which specific variable (e.g., “parental income”) is associated with which \(X_{ki}\) in the model
- usually \(X_{1i}\) would be your “independent variable of interest” (assuming it is a continuous variable or a two-category categorical variable)
- but it doesn’t really matter which specific variable is associated with which \(X_{ki}\) as long as you make it clear to your reader (and yourself!!!)
- You don’t need to define what \(\beta_k\) means because that’s just the population regression coefficient associated with a particular variable \(X_{ki}\)
Things we do in regression; all work the same in multivariate!
- Estimation
- Choose estimates for \(\beta_0, \beta_1, \beta_2, ... \beta_k\) by selecting those that minimize the sum of squared errors (i.e., make the best prediction of Y), yielding an OLS line
- \(\hat{Y_i} = \hat{\beta_0} + \hat{\beta_1} X_{1i} + \hat{\beta_2} X_{2i} + ... \hat{\beta_k} X_{ki}\)
- Choose estimates for \(\beta_0, \beta_1, \beta_2, ... \beta_k\) by selecting those that minimize the sum of squared errors (i.e., make the best prediction of Y), yielding an OLS line
- Measures of model fit (e.g., \(R^2\), SER)
- But formulas change slightly to account for “degrees of freedom”
- Once you introduce multiple independent variables, use adjusted R-squared
- Adjusted R-squared
- Adjusted for the number of predictors in the model
- Every independent variable we add to the model will increase our “normal” R-squared; but doesn’t necessarily mean it’s a better fit
- Adjusted R squared increases only if new variable improves the model more than would be expected by chance
- Prediction
- Once you estimate OLS regression line, we can calculate predicted values for observations with particular values of all independent variables
- \(\hat{Y_i} = \hat{\beta_0} + \hat{\beta_1} X_{1i} + \hat{\beta_2} X_{2i} + ... \hat{\beta_k} X_{ki}\)
- Once you estimate OLS regression line, we can calculate predicted values for observations with particular values of all independent variables
- Hypothesis testing and confidence intervals about \(\beta_1\)
- Same as before but formulas for \(\hat{\beta_1}\) and \(SE(\hat{\beta_1})\) change slightly, but R calculates this for us!
6.2 Conditional independence assumption (CIA)
OLS Assumption 1: Conditional Independence Assumption
- OLS Assumption 1 (in words)
- the independent variable \(X_i\) is unrelated to the “other variables” not included in the model, \(u_i\)
- OLS Assumption 1 (mathematically)
- \(E(u_i|X_i)=0\); the expected value of \(u_i\), given any value of \(X_i\), equals zero
Omitted variable bias
- Omitted variable bias is bias in \(\hat{\beta_1}\) due to variables being omitted from the model
- For omitted variable bias to occur, the omitted variable “Z” must satisfy two conditions
- \(Z\) affects value of Y (i.e. Z is part of \(u_i\))
- and \(Z\) has a relationship with \(X\)
Multivariate regression helps us meet the conditional independence assumption by including variables in our model whose exclusion would result in omitted variable bias
- The modeling goal is that, after including “control variables” in our model (those that meet both conditions of omitted variable bias), “treated units” (\(X_{1i}==1\) ) are on average the same as “untreated units” (\(X_{1i}==0\) ) except for the value of variable \(X_{1i}\)
Conditional Independence Assumption in evaluation of the Mexican American Studies (MAS) Program
Cabrera, N. L., Milem, J. F., Jaquette, O., & Marx, R. (2014). Missing the (student achievement) forest for all the (political) trees: Empiricism and the Mexican American Studies controversy in Tucson. American Educational Research Journal, 51(6), 1084-1118.
- Research question
- What is the effect of participating in Mexican American Studies program (MAS) on academic achievement (measured as score on high school exit exam)?
- \(Y_i = \beta_0 + \beta_1X_{1i} + \beta_2X_{2i} + \beta_3X_{3i} + u_i\), where:
- Y= High school exit exam score
- X1 = 0/1 MAS participation [non-reference group]; Did not participate in MAS [reference group]
- students can participate in MAS in 11th grade
- X2= previous academic achievement
- academic achievement prior to 11th grade
- X3= socioeconomic status
- The causal inference problem:
- we want to know the causal effect of MAS on Y
- But we have to account for the fact that students choose to participate in MAS (self-selection bias); they were not randomly assigned to participate versus not participate in MAS!
- Goal is to recreate “experimental conditions” by adding “control variables” to our model; after including control variables MAS participants are (in theory) the same as non-participants, except for participation in MAS
- Conditional independence assumption:
- Once we include control variables, there are no longer any omitted variables, Z, that satisfy both of these two conditions:
- Z affects value of Y and
- Z has a relationship with X
- Once we include control variables, there are no longer any omitted variables, Z, that satisfy both of these two conditions:
- so we try to include all “control variables” that satisfy both conditions of omitted variable bias;
- If we satisfy the conditional independence assumption through control variables, then multivariate regression is just as good as randomized assignment experiment!
- if we fail to include important control variables (because we don’t have access to them), our results suffer from omitted variable bias
- Warning: But we often don’t have every single control variable we need, so we get as close as possible!
Multivariate regression in Econometrics vs traditional social science statistics
- \(Y_i = \beta_0 + \beta_1X_{1i} + \beta_2X_{2i} + \beta_3X_{3i} + u_i\)
- Econometrics/causal inference
- We are only interested in estimating \(\beta_1\) [the causal effect of \(X_{1i}\) on Y]
- The primary reason we include other variables in the model besides X1 is to eliminate omitted variable bias
- Therefore, we include all control variables that satisfy both conditions of omitted variable bias
- Once we include control variables, and no other variables satisfy both conditions, then we satisfy the conditional independence assumption and we can estimate a causal effect!
- Traditional social science statistics [most of my research!]
- Purpose of multiple regression is to add new variable to your model (e.g., \(X_3\)) to see the effect of \(X_3\) on Y
- Can lead to sloppy research if we take a “throw” everything and the kitchen sink into a model and see what’s interesting!
- We’ll read example of this kind of research:
- Powers (2004)
“Good” vs. “bad” research
- “Good” research
- Goal is to estimate causal effects and you are thoughtful about including control variables to minimize omitted variable bias
- Goal is to understand correlational/associational relationship between \(X\) variables and \(Y\), and when interpretating results, you are careful to talk about “association” rather than “causal effect”
- “Bad” research
- Goal is to estimate causal effects but researcher isn’t thoughtful about which control variables should be included in the model
- Goal is to understand correlational/associational relationships but the author inteprets regression coefficients as if they represent causal relationships
6.3 Interpretation
Research question we will use to practice interpretation of multivariate regression, using data frame df_els_stu_fac:
[observational design, categorical \(X\)] What is the effect of having an internship or co-op job (\(X\)) (in 2005-06) on subsequent earnings (\(Y\)) (in 2011)?
- \(X\) is
f2intern0506- label: 0/1 (no/yes) held an internship or co-op in 2005-06; NA if not enrolled in postsecondary education in 2005-06
- Note: 2005-06 would be sophomore year for students who graduated HS in spring 2004 and immediately entered postsecondary education
- variable
df_els_stu_fac$f2intern0506is a factor variable with factor levels'no'and'yes'
- \(Y\) is
f3ern2011- label: 2011 employment income: R only
- sample: students who were enrolled in postsecondary education in 2005-06 (this is when question about internship was asked)
filter(f2enroll0506=='yes')
Identify a couple of “control variables” (often referred to “covariates”) to add to our model
We want to recreate “experimental conditions” (students randomly assigned to internship)
- Our goal is: after controlling for covariates, students who participate in internships are, on average, the same as students who do not participate in internships with respect to 2011 earnings, except for participation in internship
- We include control variables that we think (based on logical argument, past research, descriptive stats) satisfy both conditions of omitted variable bias:
- For omitted variable bias to occur, the omitted variable “Z” must satisfy two conditions
- \(Z\) affects value of Y (i.e. Z is part of \(u_i\))
- and \(Z\) has a relationship with \(X\)
- For omitted variable bias to occur, the omitted variable “Z” must satisfy two conditions
We’ll add one continuous control variable and two categorical control variable
- [continuous] Let’s pretend that
bytxrstd(standardized reading test score) is a measure of high school student achievement- Does high school student achievement affect subsequent earnings? (omitted variable bias condition 1)
- Yes!
- Might high school student achievement have a relationship with whether a student has an internship in college? (omitted variable bias condition 2)
- Seems possible. Maybe students with higher achievement are more likely to seek out internships (but it could be the opposite!); maybe employers are more likely to give internship opportunities to students with higher achievement
- Does high school student achievement affect subsequent earnings? (omitted variable bias condition 1)
- [categorical control] sex (
f1sex; with values “Male” and “Female”)- Does sex affect subsequent earnings? (omitted variable bias condition 1)
- Yes; well documented sex/gender discrimination in pay
- Might sex have a relationship with whether a student has an internship in college? (omitted variable bias condition 2)
- Seems possible that there is sex/gender discrimination in who gets access to internships
- Does sex affect subsequent earnings? (omitted variable bias condition 1)
- [categorical control] race (
f1race_v2)- Does race affect subsequent earnings? (omitted variable bias condition 1)
- Yes; well documented racial discrimination in pay
- Might race have a relationship with whether a student has an internship in college? (omitted variable bias condition 2)
- Seems very plausible that there is racial discrimination in who gets access to internships
- Does race affect subsequent earnings? (omitted variable bias condition 1)
- Some brief descriptive statistics of these control variables for our analysis sample
- note that for categorical “factor” class variables; the category with the lowest underlying integer value is automatically the “reference” group
# reading test score
df_els_stu_fac %>% filter(f2enroll0506=='yes') %>% summarize(
min_read = min(bytxrstd, na.rm = TRUE),
mean_read = mean(bytxrstd, na.rm = TRUE),
max_read = max(bytxrstd, na.rm = TRUE),
sd_read = sd(bytxrstd, na.rm = TRUE)
)
#> # A tibble: 1 x 4
#> min_read mean_read max_read sd_read
#> <dbl+lbl> <dbl> <dbl+lbl> <dbl>
#> 1 24.2 54.4 78.8 9.03
# sex
df_els_stu_fac %>% filter(f2enroll0506=='yes') %>% count(f1sex)
#> # A tibble: 2 x 2
#> f1sex n
#> <fct> <int>
#> 1 Male 3225
#> 2 Female 4094
# sex, show underlying integer values
df_els_stu_fac %>% filter(f2enroll0506=='yes') %>% count(as.integer(f1sex))
#> # A tibble: 2 x 2
#> `as.integer(f1sex)` n
#> <int> <int>
#> 1 1 3225
#> 2 2 4094
# race
df_els_stu_fac %>% filter(f2enroll0506=='yes') %>% count(f1race_v2)
#> # A tibble: 6 x 2
#> f1race_v2 n
#> <fct> <int>
#> 1 white 4629
#> 2 api 820
#> 3 black 768
#> 4 latinx 776
#> 5 native 35
#> 6 multi 291
# race, show underlying integer values
df_els_stu_fac %>% filter(f2enroll0506=='yes') %>% count(as.integer(f1race_v2))
#> # A tibble: 6 x 2
#> `as.integer(f1race_v2)` n
#> <int> <int>
#> 1 1 4629
#> 2 2 820
#> 3 3 768
#> 4 4 776
#> 5 5 35
#> 6 6 291Review interpretation for Bivariate regression model
- run bivariate regression
intern_mod1 <- lm(formula = f3ern2011 ~ f2intern0506, data = df_els_stu_fac %>% filter(f2enroll0506=='yes'))
summary(intern_mod1)
#>
#> Call:
#> lm(formula = f3ern2011 ~ f2intern0506, data = df_els_stu_fac %>%
#> filter(f2enroll0506 == "yes"))
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -33863 -16764 -3764 11236 221236
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 28763.9 296.7 96.937 < 0.0000000000000002 ***
#> f2intern0506yes 5099.2 1195.8 4.264 0.0000203 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 24570 on 7306 degrees of freedom
#> (11 observations deleted due to missingness)
#> Multiple R-squared: 0.002483, Adjusted R-squared: 0.002346
#> F-statistic: 18.18 on 1 and 7306 DF, p-value: 0.00002031- Population linear regression model (bivariate regression)
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ u_i\), where:
- \(Y_i\): is earnings for student \(i\) in 2011
- \(X_{1i}\): is a dichotomous categorical variable indicating whether student \(i\) had an internship in the 2005-06 academic year
- \(u_i\) is all variables that affect \(Y_i\) but were not included in our model
- \(Y_i\): is earnings for student \(i\) in 2011
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ u_i\), where:
- OLS prediction line
- without estimates
- \(\hat{Y_i} = \hat{\beta_0} + \hat{\beta_1}X_i\)
- with estimates
- \(\hat{Y_i} =\) 28,764 + 5,099 \(\times X_i\)
- without estimates
- Interpretation of \(\hat{\beta_1}\) for categorical \(X_1\)
- Generic:
- “being [specific non-reference category] as opposed to [reference category] is, on average, associated with a \(\hat{\beta_1}\) change in \(Y\)”
- Specific interpretation of \(\hat{\beta_1}=\) 5,099
- having an internship as opposed to not having an internship is, on average, associated with a 5,099 dollar change in annual earnings
- Generic:
- Interpretation of \(\hat{\beta_0}\)
- Generic:
- \(\hat{\beta_0}\) is the estimated average value of the outcome, \(\hat{Y_i}\), when all independent variables \(X_{1i},X_{2i},\ldots X_{ki}\) equal
0 - Note: for categorical independent variables, “equals
0” means being the category associated with the reference group
- \(\hat{\beta_0}\) is the estimated average value of the outcome, \(\hat{Y_i}\), when all independent variables \(X_{1i},X_{2i},\ldots X_{ki}\) equal
- Specific interpretation of \(\hat{\beta_0}=\) 28,764
- The estimated average 2011 earnings for students who did not have an internship is 28,764
- Generic:
Multivariate regression
run multivariate regression model, adding control variables bytxrstd (reading achievement, continuous), f1sex (sex, categorical), and f1race_v2 (race, categorical) to the model
- syntax for
lmfunction:lm(formula = yvar ~ xvar1 + xvar2 + xvar3, data = data_frame_name)
intern_mod2 <- lm(formula = f3ern2011 ~ f2intern0506 + bytxrstd + f1sex + f1race_v2, data = df_els_stu_fac %>% filter(f2enroll0506=='yes'))
summary(intern_mod2)
#>
#> Call:
#> lm(formula = f3ern2011 ~ f2intern0506 + bytxrstd + f1sex + f1race_v2,
#> data = df_els_stu_fac %>% filter(f2enroll0506 == "yes"))
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -39866 -16030 -2796 11198 225259
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 22418.27 1911.29 11.729 < 0.0000000000000002 ***
#> f2intern0506yes 5640.81 1181.46 4.774 0.00000183704 ***
#> bytxrstd 199.98 32.96 6.067 0.00000000137 ***
#> f1sexFemale -5925.57 571.29 -10.372 < 0.0000000000000002 ***
#> f1race_v2api -1371.74 924.35 -1.484 0.1379
#> f1race_v2black -4885.98 975.53 -5.009 0.00000056138 ***
#> f1race_v2latinx -4214.37 960.21 -4.389 0.00001154844 ***
#> f1race_v2native -10133.31 4118.80 -2.460 0.0139 *
#> f1race_v2multi -2080.70 1464.50 -1.421 0.1554
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 24220 on 7299 degrees of freedom
#> (11 observations deleted due to missingness)
#> Multiple R-squared: 0.03188, Adjusted R-squared: 0.03082
#> F-statistic: 30.05 on 8 and 7299 DF, p-value: < 0.00000000000000022- Population linear regression model (multivariate regression)
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ \beta_2 X_{2i}+ \beta_3 X_{3i}+ \beta_4 X_{4i}+ \beta_5 X_{5i}+ \beta_6 X_{6i}+ \beta_7 X_{7i}+ \beta_8 X_{8i}+ u_i\), where:
- \(Y_i\): is earnings for student \(i\) in 2011 (in dollars)
- \(X_{1i}\): is a dichotomous categorical variable indicating whether student \(i\) had an internship in 2005-06
- \(X_{2i}\): (continuous) high school reading test score
- \(X_{3i}\): (dichotomous) student \(i\) identifies as female
- \(X_{4i}\): (dichotomous) student \(i\) identifies as Asian or Pacific Islander (API)
- \(X_{5i}\): (dichotomous) student \(i\) identifies as Black
- \(X_{6i}\): (dichotomous) student \(i\) identifies as Latinx
- \(X_{7i}\): (dichotomous) student \(i\) identifies as Native American
- \(X_{8i}\): (dichotomous) student \(i\) identifies as two or more races
- \(u_i\) is all variables that affect \(Y_i\) but were not included in our model
- \(Y_i\): is earnings for student \(i\) in 2011 (in dollars)
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ \beta_2 X_{2i}+ \beta_3 X_{3i}+ \beta_4 X_{4i}+ \beta_5 X_{5i}+ \beta_6 X_{6i}+ \beta_7 X_{7i}+ \beta_8 X_{8i}+ u_i\), where:
- OLS prediction line
- without estimates
- \(\hat{Y_i} = \hat{\beta_0} + \hat{\beta_1}X_i + \hat{\beta_2} X_{2i}+ \hat{\beta_3} X_{3i}+ \hat{\beta_4} X_{4i}+ \hat{\beta_5} X_{5i}+ \hat{\beta_6} X_{6i}+ \hat{\beta_7} X_{7i}+ \hat{\beta_8} X_{8i}\)
- with estimates
- \(\hat{Y_i} =\) 22,418 + 5,641 \(\times X_{1i}\) + 200 \(\times X_{2i}\) + -5,926 \(\times X_{3i}\) + -1,372 \(\times X_{4i}\) + -4,886 \(\times X_{5i}\) + -4,214 \(\times X_{6i}\) + -10,133 \(\times X_{7i}\) + -2,081 \(\times X_{8i}\)
- without estimates
Interpretation \(\hat{\beta_k}\)
Interpretation of \(\hat{\beta_k}\) from multivariate regression is almost exactly the same as interpretation from bivariate regression
Interpretation of \(\hat{\beta_k}\) (for continuous variable \(X_k\))
- Generic:
- “a one-unit increase in \(X_k\) is associated with a \(\hat{\beta_k}\) change in Y, holding the value of all other \(X\) variables constant”
- For high school reading test score \(X_{2i}\), \(\hat{\beta_2}=\) 200
- a one-point increase in high school reading test score is associated with a 200 dollar change in 2011 earnings, holding the value of all other \(X\) variables constant
Interpretation of \(\hat{\beta_k}\) (for categorical variable \(X_k\))
- Generic:
- “being [specific non-reference category] as opposed to [reference category] is, on average, associated with a \(\hat{\beta_k}\) change in \(Y\), holding the of value all other \(X\) variables constant”
- For participation in internship \(X_{1i}\), \(\hat{\beta_1}=\) 5,641
- having an internship as opposed to not having an internship is, on average, associated with a 5,641 dollar change in annual earnings, holding the value of all other \(X\) variables constant
What does “holding constant” mean?
- “Holding the value of all other \(X\) variables constant” means to estimate the relationship between \(X_1\) (internship) and \(Y\) when we we don’t allow the values of \(X_2\) (high school reading test score) to vary (and we don’t allow any other \(X\) variables to vary)
- In other words, we analyze the relationship between having an internship \(X_1\) and earnings (\(Y\)) for students who have the same value for high school reading test score (\(X_2\)), the same value for sex (\(X_3\)), the same value for “identify as API” (\(X_4\)), etc.
- Mathematically, “holding constant” is achieved through calculus (partial derivatives)
Relationship between “holding constant” and attempting to recreate experimental conditions
We use multivariate regression to try to recreate experimental conditions (students randomly assigned to participate in internships)
In a true experiment, both students randomly assigned to an internship and students randomly assigned to not have an internship would, on average, have the same values for other variables that affect earnings \(Y\) (e.g,. gender, race, parental income)
In multivariate regression, we add “control variables” (variables that satisfy both conditions of omitted variable bias) so that we can examine the relationship between having an internship (\(X_1\)) and earnings (\(Y\)) for students who have the same value for other variables thought to affect earnings
- Means to estimate the relationship between \(X_1\) and Y when we don’t allow the value of \(X_2\) to vary
More practice interpreting \(\hat{\beta_k}\) (for categorical \(X\))
- Population linear regression model (multivariate regression)
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ \beta_2 X_{2i}+ \beta_3 X_{3i}+ \beta_4 X_{4i}+ \beta_5 X_{5i}+ \beta_6 X_{6i}+ \beta_7 X_{7i}+ \beta_8 X_{8i}+ u_i\), where:
- \(Y_i\): is earnings for student \(i\) in 2011 (in dollars)
- \(X_{1i}\): is a dichotomous categorical variable indicating whether student \(i\) had an internship in 2005-06
- \(X_{2i}\): (continuous) high school reading test score
- \(X_{3i}\): (dichotomous) student \(i\) identifies as female
- \(X_{4i}\): (dichotomous) student \(i\) identifies as Asian or Pacific Islander (API)
- \(X_{5i}\): (dichotomous) student \(i\) identifies as Black
- \(X_{6i}\): (dichotomous) student \(i\) identifies as Latinx
- \(X_{7i}\): (dichotomous) student \(i\) identifies as Native American
- \(X_{8i}\): (dichotomous) student \(i\) identifies as two or more races
- \(u_i\) is all variables that affect \(Y_i\) but were not included in our model
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ \beta_2 X_{2i}+ \beta_3 X_{3i}+ \beta_4 X_{4i}+ \beta_5 X_{5i}+ \beta_6 X_{6i}+ \beta_7 X_{7i}+ \beta_8 X_{8i}+ u_i\), where:
- OLS prediction line
- without estimates
- \(\hat{Y_i} = \hat{\beta_0} + \hat{\beta_1}X_i + \hat{\beta_2} X_{2i}+ \hat{\beta_3} X_{3i}+ \hat{\beta_4} X_{4i}+ \hat{\beta_5} X_{5i}+ \hat{\beta_6} X_{6i}+ \hat{\beta_7} X_{7i}+ \hat{\beta_8} X_{8i}\)
- with estimates
- \(\hat{Y_i} =\) 22,418 + 5,641 \(\times X_{1i}\) + 200 \(\times X_{2i}\) + -5,926 \(\times X_{3i}\) + -1,372 \(\times X_{4i}\) + -4,886 \(\times X_{5i}\) + -4,214 \(\times X_{6i}\) + -10,133 \(\times X_{7i}\) + -2,081 \(\times X_{8i}\)
- without estimates
Interpretation of \(\hat{\beta_k}\) (for categorical variable \(X_k\))
- Generic:
- “being [specific non-reference category] as opposed to [reference category] is, on average, associated with a \(\hat{\beta_k}\) change in \(Y\), holding the of value all other \(X\) variables constant”
- Conceptually, we have two categorical control variables in our model; the first is sex, where the reference group is “male”; the second is race, where the reference group is “white”
- \(X_{3i}\) (identifies as female); \(\hat{\beta_3}=\) -5,926
- being female as opposed to male is associated with a -5,926 dollar change in 2011 earnings, holding the of value all other \(X\) variables constant
- \(X_{4i}\) (identifies as Asian or Pacific Islander (API)); \(\hat{\beta_4}=\) -1,372
- being API as opposed to white is associated with a -1,372 dollar change in 2011 earnings, holding the of value all other \(X\) variables constant
- \(X_{5i}\) (identifies as Black); \(\hat{\beta_5}=\) -4,886
- being Black as opposed to white is associated with a -4,886 dollar change in 2011 earnings, holding the of value all other \(X\) variables constant
- \(X_{6i}\) (identifies as Latinx); \(\hat{\beta_6}=\) -4,214
- You do the rest!
- \(X_{7i}\) (identifies as Native American); \(\hat{\beta_7}=\) -10,133
- \(X_{8i}\) (identifies as two or more races; \(\hat{\beta_8}=\) -2,081
Interpretation of \(\hat{\beta_0}\) in multivariate regression
- Conceptually, the same as interpretation for bivariate regression
- \(\hat{\beta_0}\) is the estimated average value of the outcome, \(\hat{Y_i}\), when all independent variables \(X_{1i},X_{2i},\ldots X_{ki}\) equal
0- Note: for categorical independent variables, “equals
0” means being the category associated with the reference group
- Note: for categorical independent variables, “equals
- Specific interpretation of \(\hat{\beta_0}=\) 22,418
- The estimated average 2011 earnings for white, male students who did not have an internship and who got a score of
0on the high school reading test is 22,418
- The estimated average 2011 earnings for white, male students who did not have an internship and who got a score of
Prediction (still works the same way!)
- Population linear regression model (multivariate regression)
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ \beta_2 X_{2i}+ \beta_3 X_{3i}+ \beta_4 X_{4i}+ \beta_5 X_{5i}+ \beta_6 X_{6i}+ \beta_7 X_{7i}+ \beta_8 X_{8i}+ u_i\), where:
- \(Y_i\): is earnings for student \(i\) in 2011 (in dollars)
- \(X_{1i}\): is a dichotomous categorical variable indicating whether student \(i\) had an internship in 2005-06
- \(X_{2i}\): (continuous) high school reading test score
- \(X_{3i}\): (dichotomous) student \(i\) identifies as female
- \(X_{4i}\): (dichotomous) student \(i\) identifies as Asian or Pacific Islander (API)
- \(X_{5i}\): (dichotomous) student \(i\) identifies as Black
- \(X_{6i}\): (dichotomous) student \(i\) identifies as Latinx
- \(X_{7i}\): (dichotomous) student \(i\) identifies as Native American
- \(X_{8i}\): (dichotomous) student \(i\) identifies as two or more races
- \(u_i\) is all variables that affect \(Y_i\) but were not included in our model
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ \beta_2 X_{2i}+ \beta_3 X_{3i}+ \beta_4 X_{4i}+ \beta_5 X_{5i}+ \beta_6 X_{6i}+ \beta_7 X_{7i}+ \beta_8 X_{8i}+ u_i\), where:
- OLS prediction line
- without estimates
- \(\hat{Y_i} = \hat{\beta_0} + \hat{\beta_1}X_i + \hat{\beta_2} X_{2i}+ \hat{\beta_3} X_{3i}+ \hat{\beta_4} X_{4i}+ \hat{\beta_5} X_{5i}+ \hat{\beta_6} X_{6i}+ \hat{\beta_7} X_{7i}+ \hat{\beta_8} X_{8i}\)
- with estimates
- \(\hat{Y_i} =\) 22,418 + 5,641 \(\times X_{1i}\) + 200 \(\times X_{2i}\) + -5,926 \(\times X_{3i}\) + -1,372 \(\times X_{4i}\) + -4,886 \(\times X_{5i}\) + -4,214 \(\times X_{6i}\) + -10,133 \(\times X_{7i}\) + -2,081 \(\times X_{8i}\)
- without estimates
What is the predicted 2011 earnings for a student who participated in an internship (\(X_{1i}=1\)), who scored 65 on the high school reading test (\(X_{2i}=65\)), who identifies as female (\(X_{3i}=1\)), and who identifies as Latinx (\(X_{6i=1}\))?
- \(\hat{Y_i} = \hat{\beta_0} + \hat{\beta_1}\times 1 + \hat{\beta_2} \times 65 + \hat{\beta_3} \times 1 + \hat{\beta_4} \times 0+ \hat{\beta_5} \times 0+ \hat{\beta_6} \times 1 + \hat{\beta_7} \times 0 + \hat{\beta_8} \times 0\)
- \(\hat{Y_i} = \hat{\beta_0} + \hat{\beta_1}\times 1 + \hat{\beta_2} \times 65 + \hat{\beta_3} \times 1 + \hat{\beta_6} \times 1\)
- \(\hat{Y_i} =\) 22,418 + 5,641\(\times 1\) + 200\(\times 65\) + -5,926\(\times 1\) + -4,214$1 = $ 30,918
What is the predicted 2011 earnings for a student who participated in an internship (\(X_{1i}=1\)), who scored 45 on the high school reading test (\(X_{2i}=45\)) and who identifies as white, who identifies as male?
- \(\hat{Y_i} = \hat{\beta_0} + \hat{\beta_1}\times 1 + \hat{\beta_2} \times 45 + \hat{\beta_3} \times 0 + \hat{\beta_4} \times 0+ \hat{\beta_5} \times 0+ \hat{\beta_6} \times 0 + \hat{\beta_7} \times 0 + \hat{\beta_8} \times 0\)
- \(\hat{Y_i} = \hat{\beta_0} + \hat{\beta_1}\times 1 + \hat{\beta_2} \times 45\)
- \(\hat{Y_i} =\) 22,418 + 5,641 \(\times 1 +\) 200 \(\times 45 =\) 37,058
7 Reading Empirical Regression Results
Our first example of empirical regression results
Powers, J. M. (2004). High-Stakes Accountability and Equity: Using Evidence From California’s Public Schools Accountability Act to Address the Issues in Williams v. State of California. American Educational Research Journal, 41(4), 763–795.
- RQ: What is relationship between school resource variables and school-level academic performance index (API)?
- Does not frame article as “causal inference” but Powers is doing exactly what we have learned in this lecture/class!
- Attempts to analyze the effect of school resources (X) on the academic achievement of schools (Y) by controlling for variables that would be “systematically related” to the independent variables of interest and have an effect on the dependent variable
- Does not have all possible controls to get to a “causal effect” equivalent to what we would estimate if the study was designed as an randomized control experiment.
How to read a methods section…
- The format of quantitative empirical research is pretty “standardized”, which makes it easy to read as you get more experience…
- Methods section usually outlines the data used, sample, variables, and the methods used
For Powers (2004):
- Data: uses data similar to our
caschools(ours is district level; Powers uses school-level!) - Sample: All CA schools that were assigned an API score
- 97% of full population of CA schools
- Variables: provides details on all the variables in the model!
- Pay attention to how variables are constructed!
- Note that sometimes we don’t have a variable we need, so we use a “proxy.” It’s the authors’ responsibility to convince readers why the variable used is a good enough proxy for the unavailable variable needed
- Empirical studies use a lot of variables in the model which are difficult to keep track of; so they are often “grouped” into categories (e.g., student characteristics, school resources, etc)
- Methodology: This section varies depending on the sophistication of the method.
- Sometimes they write out the full population regression model, sometimes they don’t
- Linear regression is considered simple so in most cases they don’t
How to read results (descriptives)…
- Quantitative research studies nearly always present the descriptive statistics of all variables used in a table
- In most cases the mean and standard deviation is sufficient; if it’s substantively important sometimes min and max (or can be covered within text of the variables sub-section of the methods section)
- Sometimes authors dedicate space within text to explaining descriptive stats and sometimes they don’t
- Usually depends on how substantively important they are…
- Most folks can read the table so authors will avoid spending too much limited space on descriptive statistics
How to read results (regression models)…
- The way in which regression results are presented is well standardized across all fields and journals! [some exceptions]
- Regression tables usually show the beta coefficient and standard error (usually in parentheses) for each independent variable
- Columns are individual models
- Tables usually start with a simple regression model in the first column that only includes the main independent variable(s) of interest: “model 1”
- Then add control variables incrementally; sometimes done in groupings
- This allows the author to show the “progression” in the models as variables are added in (particularly important for descriptive research to see changes in model fit statistics)
- Although, sometimes models in separate columns can also indicate various samples; look at the headings/read the authors description of table
- Read the table notes
- Provide the key for interpreting the significance levels of p-values as denoted by asterisks ( \(*p\le 0.05\), \(**p\le 0.01\),\(***p\le 0.001\) )
- Will also tell you what the reference category is for categorical variables!
- Other useful information
- Table 2: Nested Regression Models Using 1999 API Index as DV, pg. 781
- The most “standard way” to format regression results
- You show the “progression” towards your final regression model via multiple models
- Intercept-only model (no independent variables) [Powers didnt show this]
- Model 1 can have your independent variable of interest (standard for program eval) or some variables (Powers did student characteristics)
- Models 2+… shows the addition of control variables
- Shows beta coefficients, standard errors, and significant levels!
Interpretation for Table 2 for Williams Case Variables
- In text, she hardly interprets beta coefficients beyond “significance and direction”
- Only sometimes mentions the magnitude of the coefficient
- This approach is common in “descriptive research”
- Dependent variable, \(Y_i\) is “Academic performance index” for school \(i\)
- “dependent variable for all analyses is the state constructed API index. This summary score for each school was constructed by weighting student scores in each content area of the SAT-9 test by their national percentile ranking (NPR), and then weighting each content area to create an overall score (California Department of Education Office of Policy and Evaluation, 2000)…”
- Teacher training (reference group is fully credentialed teachers)
- Emergency Credentialed \(\hat{\beta}\) Coefficient: -1.12*** SE= 0.09
- Interpretation: “On average, one-percentage-point increase in a school teaching staff’s proportion of emergency credentialed teachers (as opposed to fully credentialed teachers) is associated with a 1.12 point decrease in API score, holding all covariates constant”
- Emergency Credentialed \(\hat{\beta}\) Coefficient: -1.12*** SE= 0.09
- Teacher Experience
- Years teaching \(\hat{\beta}\) Coefficient: .80** SE= 0.26
- Interpretation: “A one year increase in a school teaching staff’s average years of experience, on average, is associated with a 0.80 point increase in API score, holding all covariates constant”
- Interpretation: “A one year increase in a school teaching staff’s average years of experience, on average, is associated with a 0.80 point increase in API score, holding all covariates constant”
- Years teaching \(\hat{\beta}\) Coefficient: .80** SE= 0.26
- Teacher Education (reference group is less than M.A)
- Greater than MA \(\hat{\beta}\) Coefficient: .42*** SE= 0.06
- Interpretation: “On average, a one-percentage-point increase in a school teaching staff’s proportion of teachers with greater than MA degree (as opposed to lower than MA teachers) is associated with a 0.42 point increase in API score, holding all covariates constant”
- Greater than MA \(\hat{\beta}\) Coefficient: .42*** SE= 0.06
- School Calendar (reference group is traditional year)
- Concept 6 \(\hat{\beta}\) Coefficient: -34.46*** SE= 4.52
- Interpretation: “On average, being a school with a Concept 6 Calendar as opposed to a Traditional Calendar is associated with a 34.46 point decrease in API score, holding all covariates constant”
- Concept 6 \(\hat{\beta}\) Coefficient: -34.46*** SE= 4.52
- Textbooks
- Per-pupil textbook expenditures \(\hat{\beta}\) Coefficient: .11*** SE=0.003
- Interpretation: “A $1 increase in per-pupil expenditures for textbooks is associated with a 0.1 point increase in API score, holding all covariates constant”
- Interpretation: “A $10 increase in per-pupil expenditures for textbooks, on average, is associated with a 1 point increase in API score, holding all covariates constant”
- Interpretation: “A $100 increase in per-pupil expenditures for textbooks, on average, is associated with a 10 point increase in API score, holding all covariates constant”
- Interpretation: “A $1 increase in per-pupil expenditures for textbooks is associated with a 0.1 point increase in API score, holding all covariates constant”
- Per-pupil textbook expenditures \(\hat{\beta}\) Coefficient: .11*** SE=0.003
- Table 2 shows model fit statistics!
- Powers is not writing from a program evaluation standpoint
- Rather she’s trying to show how variables from Williams Case explain (predict!) API scores
- In this case, measures of model fit are important
- \(R^2\) increases from Model 1 to Model 2
- Change in \(R^2\) doesn’t mean that Williams case IVs add “little” explanation; see pg 782!
- In text, she mentions overall F-test is significant from Model 1 to Model 2
- F-test is related to \(R^2\)
- \(H_0\): model with no independent variables (or limited IVs) fits the data just as well as model with full variables
- \(H_a\): model with more variables fits the data better than model with no IVs
8 Linear Probability Model
Linear Probability Model
- Binary Variables (i.e., dummies, indicators) as dependent variables are very common in education research!
- Y = Retention (0=dropped out, 1= persisted)
- Y = Graduation (0= did not graduate, 1= graduated)
- Y = Pass/Fail (0=Failed, Passed=1)
- Regression models with a binary dependent variable attempt to interpret the effect of X on the probability of “success” (Y=1)
- Or in some cases the probability of “failure”
- Most social science disciplines model binary dependent variables via non-linear regression models
- most common model for 0/1 dependent variables is logistic regression, but interpretation can be difficult because coefficients measured in “log odds”
- Econometric models typically model binary dependent variables using linear probability model
- Population parameters can be estimated via OLS!
- Simple to estimate and interpret!
- Only “tool” that doesn’t carry over? \(R^2\); but program evaluation is less concerned with model fit than hypothesis testing about the population parameter \(\beta_1\)
- It can ONLY be used for binary, categorical dependent variables
- If more than two categories, then we have to use different models (e.g., multinomial logistic regression)
8.1 Interpretation of \(\hat{\beta_k}\)
“percentage point change” vs. “percentage change”
- When interpreting \(\hat{\beta_k}\) for the linear probability model (below) we refer to a “percentage point change in the probability that \(Y=1\)”
- “Percentage point change” is percentage A minus percentage B (or vice versa)
- Example, using Mexican American Studies (MAS) program offered by Tucson Unified School District
- Imagine that high school students who participate in the Mexican American Studies (MAS) program have a 68% probability of graduating from high school and students who do not participate in MAS have a 60% probability of graduating from high school.
- The “percentage point change” in the probability of graduating from high school associated with participating in MAS is: \(68\% - 60\%= 8\%\)
- Example, using Mexican American Studies (MAS) program offered by Tucson Unified School District
- “percentage change” expresses the difference between final and initial values
- imagine that \(Y_1\) and \(Y_2\) are two different values of some variable
- percentage change is calculated as \(\frac{Y_2 - Y_1}{Y_1} \times 100\)
- Example:
- imagine that \(Y_1= \$4.00\) is the price of one gallone of gas last year and \(Y_2= \$6.00\) is the price of a gallon of gas this year
- the percentage change is \(\frac{Y_2 - Y_1}{Y_1} \times 100 = \frac{6 - 4}{4} \times 100 =50\)
- we would say, the price of gas has increased by 50% from last year to this year
- For interpretation of the linear probability model we use percentage point change rather than percentage change
Run regression model with participation in internship as Y-variable and following X-variables:
- high school reading score (continuous), parent income (continuous), sex (dichotomous categorical), race (categorical)
intern_mod3 <- lm(formula = as.integer(f2intern0506) ~ bytxrstd + parent_income + f1sex + f1race_v2, data = df_els_stu_fac %>% filter(f2enroll0506=='yes'))
summary(intern_mod3)
#>
#> Call:
#> lm(formula = as.integer(f2intern0506) ~ bytxrstd + parent_income +
#> f1sex + f1race_v2, data = df_els_stu_fac %>% filter(f2enroll0506 ==
#> "yes"))
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -0.14436 -0.07010 -0.05808 -0.04747 0.97440
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 1.141080405698 0.018876197504 60.451 < 0.0000000000000002 ***
#> bytxrstd -0.001463088661 0.000332680861 -4.398 0.0000111 ***
#> parent_income 0.000000001466 0.000000049121 0.030 0.9762
#> f1sexFemale -0.004652650380 0.005666474240 -0.821 0.4116
#> f1race_v2api 0.006204346387 0.009193138058 0.675 0.4998
#> f1race_v2black 0.017712756824 0.009746501059 1.817 0.0692 .
#> f1race_v2latinx -0.011702592720 0.009577076265 -1.222 0.2218
#> f1race_v2native 0.047217349501 0.040823780874 1.157 0.2475
#> f1race_v2multi 0.024675822368 0.014517484379 1.700 0.0892 .
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 0.24 on 7299 degrees of freedom
#> (11 observations deleted due to missingness)
#> Multiple R-squared: 0.004838, Adjusted R-squared: 0.003747
#> F-statistic: 4.436 on 8 and 7299 DF, p-value: 0.00002248
- Population linear probability regression model (multivariate regression)
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ \beta_2 X_{2i}+ \beta_3 X_{3i}+ \beta_4 X_{4i}+ \beta_5 X_{5i}+ \beta_6 X_{6i}+ \beta_7 X_{7i}+ \beta_8 X_{8i}+ u_i\), where:
- \(Y_i\): dichotomous measure of whether student \(i\) in participated in internship/co-op in 2005-06
- \(X_{1i}\): (continuous) high school reading test score
- \(X_{2i}\): (continuous) measure of parental income
- \(X_{3i}\): (dichotomous) student \(i\) identifies as female
- \(X_{4i}\): (dichotomous) student \(i\) identifies as Asian or Pacific Islander (API)
- \(X_{5i}\): (dichotomous) student \(i\) identifies as Black
- \(X_{6i}\): (dichotomous) student \(i\) identifies as Latinx
- \(X_{7i}\): (dichotomous) student \(i\) identifies as Native American
- \(X_{8i}\): (dichotomous) student \(i\) identifies as two or more races
- \(u_i\) is all variables that affect \(Y_i\) but were not included in our model
- \(Y_i = \beta_0 + \beta_1 X_{1i}+ \beta_2 X_{2i}+ \beta_3 X_{3i}+ \beta_4 X_{4i}+ \beta_5 X_{5i}+ \beta_6 X_{6i}+ \beta_7 X_{7i}+ \beta_8 X_{8i}+ u_i\), where:
- OLS prediction line
- without estimates
- \(\hat{Y_i} = \hat{\beta_0} + \hat{\beta_1}X_i + \hat{\beta_2} X_{2i}+ \hat{\beta_3} X_{3i}+ \hat{\beta_4} X_{4i}+ \hat{\beta_5} X_{5i}+ \hat{\beta_6} X_{6i}+ \hat{\beta_7} X_{7i}+ \hat{\beta_8} X_{8i}\)
- with estimates
- \(\hat{Y_i} =\) 1.1411 + -0.0015 \(\times X_{1i}\) + 0 \(\times X_{2i}\) + -0.0047 \(\times X_{3i}\) + 0.0062 \(\times X_{4i}\) + 0.0177 \(\times X_{5i}\) + -0.0117 \(\times X_{6i}\) + 0.0472 \(\times X_{7i}\) + 0.0247 \(\times X_{8i}\)
- without estimates
Interpreting Linear Probability Model, Continuous X
- Dependent variable is a 0/1 measure of whether student participated in an internship
- Interpretation of \(\hat{\beta_k}\)
- Generic:
- On average, a one-unit increase in X is associated with a \(\hat{\beta_k}*100\) percentage point change in the probability of Y=1
- Interpretation for \(X_{1i}\) (high school reading test score); \(\hat{\beta_1}=\) -0.0015
- on average, a one-point increase in high school reading test score is associated with a -0.1463 percentage-point change in the probability of having an internship.
- that is, this is a decline in probability of receiving an internship that is less than one percentage point.
- Generic:
- Interpretation of \(\hat{\beta_k}\) when you SCALE X
- Generic:
- On average, a N-unit increase in X is associated with a ((N-unit\(*\hat{\beta_1}\))*100) percentage point change in the probability of Y=1
- Interpretation for a 10-point increase in \(X_{1i}\) (high school reading test score); \(\hat{\beta_1}=\) -0.0015
- on average, a 10-point increase in high school reading test score is associated with a -1.4631 percentage-point change in the probability of having an internship.
- that is, this is about a 1.5 percentage point decline in probability of receiving an internship (e.g., from 50.0% to 48.5% probability of receiving an internship; or going from a 30% to 28.5% chance of receiving an internship.
- Generic:
Linear Probability Model, with Categorical X
- Dependent variable is a 0/1 measure of whether student participated in an internship
- Interpretation of \(\hat{\beta_1}\)
- Generic: being in the “non-reference group” as opposed to the “reference group” is, on average, associated with a \(100*\hat{\beta_1}\) percentage point change in the probability of Y=1
- Interpretation for \(X_{8i}\) (0/1 student identies as two or more races); \(\hat{\beta_8}\) 0.0247
- (reference group is “identifies as white”)
- identifying as two-or-more races as opposed to identifying as white is, on avarage, associated with 2.4676 percentage-point change in the probability of having an internship.
- that is, this about a 2.5% increase in the probability of having an internship (e.g., from 20% to 22.5% probability of having an internship)
Interpretation of results from journal articles
Cabrera, N. L., Milem, J. F., Jaquette, O., & Marx, R. (2014). Missing the (student achievement) forest for all the (political) trees: Empiricism and the Mexican American Studies controversy in Tucson. American Educational Research Journal, 51(6), 1084-1118.
Below is partial screenshot from Table 3 from, where:
- \(Y\) = 0/1 student graduated from high school
- \(X_1\) = 0/1 student participated in the Mexican American Studies (MAS) major
And below is text interpreting results
- note that the regression coefficient of
0.095was interpreted as, participating in MAS as opposed to not participating in MAS was, on average, associated with a9.5percentage point increase in the probability of graduattion- where the
9.5is calculated as follows: \(\hat{\beta_1}*100 = .095 * 100 = 9.5\)
- where the
