index.Rmd

--- 
title: "Coding Causal Inference in R"
date: "`r Sys.Date()`"
site: bookdown::bookdown_site
documentclass: book
bibliography: book.bib
link-citations: yes
csl: american-journal-of-epidemiology.csl
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, warning = FALSE, message = FALSE)
library(knitr)
```

# About {-}

This notebook contains R code for part 2 of [*Causal Inference*](https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/) by Miguel Hernán and Jamie Robins [@hernan_causal_2019]. While R, SAS, Stata, and Python code are available on the website for *Causal Inference*, we focus on doing causal inference using the [tidyverse](https://www.tidyverse.org/) ecosystem of R packages, particularly ggplot2, dplyr, and broom. 

[This notebook is hosted on GitHub](https://github.com/malcolmbarrett/causal_inference_book); please post any issues or suggestions there.

The data used in this notebook can be downloaded from the [*Causal Inference*](https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/) website, as well as on the [GitHub repository](https://github.com/malcolmbarrett/causal_inference_book). Alternatively, cleaned versions of the data are available in the `cidata` package, which you can install from GitHub:

```r 
# if you don't have the remotes package:
# install.packages("remotes")
remotes::install_github("malcolmbarrett/cidata") 
```