1. Regression Discontinuity Design

# #setwd(“/Users/andy/desktop”)
# original post: https://towardsdatascience.com/the-crown-jewel-of-causal-inference-regression-discontinuity-design-rdd-bad37a68e786
# We are going to use simulated data to examine the treatment effect of an exogenous condition. The research question is whether receiving a scholarship would help students succeed in future professional success. 

#To generate a sample data, adn we set the cutoff point = 3.5

GPA <- runif(1000, 0, 4)
future_success <- 10 + 2 * GPA + 10 * (GPA>=3.5) + rnorm(1000)

#install and load the package ‘rddtools’
#install.packages(“rddtools”)

library(rddtools)
data <- rdd_data(future_success, GPA, cutpoint = 3.5)

# plot the dataset
plot(data,col = “red”,
 cex = 0.1, 
 xlab = “GPA”, 
 ylab = “future_success”)
 
# estimate the sharp RDD model
rdd_mod <- rdd_reg_lm(rdd_object = data, slope = “same”)
summary(rdd_mod)

# plot the RDD model along with binned observations
plot(rdd_mod,cex = 0.1, 
 col = “red”, 
 xlab = “GPA”, 
 ylab = “future_success”)