Causal Inference notebook

This notebook contains R code for part 2 of Causal Inference by Miguel HernĂ¡n and Jamie Robins. While R, SAS, Stata, and Python code are available on the website for Causal Inference, we focus on doing causal inference using the tidyverse ecosystem of R packages, particularly ggplot2, dplyr, and broom.

Malcolm Barrett
PhD Student in Epidemiology

I am an R developer and a PhD student in Epidemiology at the University of Southern California. My work in public health has spanned on-ground clinical education and research for clinical and cohort studies. Previously, I was an intern at RStudio, and I served two years in AmeriCorps at federally-qualified health centers in Michigan and New York City.