library(rstanarm)

setwd("C:/Users/az310/Dropbox/Teaching/Teach Bayesian/NCRM Intro Bayesian analysis")

rm(list=ls())
load("Turnout for logit.RData")

# logit model of turnout
# interest = interest in general election
# knowledge = correct answers to the factual questions about politics
# highschool = high school education
# badegree = Bachelor's degree or higher

## A logistic regression estimated with MLE
glm <- glm(voted ~ interest + knowledge + highschool + badegree,
           data=individual,
           family = binomial)
summary(glm)

## A logistic regression estimated using Bayesian analysis
fit <- stan_glm(voted ~ interest + knowledge + highschool + badegree,
                 data=individual,
                 family = binomial,
                 seed=1234)
## Summary of the priors
prior_summary(fit)

## Draws from the posterior distribution
draws <- as.data.frame(fit)
head(draws)
summary(draws)