useR! 2020: Causal inference in R (Lucy D'Agostino McGowan, Malcom Barrett), tutorial
Channel: R Consortium
Date: 2020-08-03

Lucy D'Agostino McGowan and Malcom Barret give a tutorial on Causal inference in R. The team covers drawing assumptions on a graph, model assumption, analyzing propensities, and estimating causal effect. Throughout the presentation there are exercises provided as well as a walk through afterwards. This video is part of the virtual useR! 2020 conference.
Find supplementary material on our website https://user2020.r-project.org/.


Main Sections 

0:00 Introduction
2:53 Three best practices of analysis
12:03 Causal modeling in R: whole game 
24:30 Diagnose your model assumptions 
27:18 Estimate the causal effects 
30:05 Using {rsample} to bootstrap our causal effect 
33:15 Review the R markdown file later! 
33:55 Resources 
35:15 Causal diagrams in R 
37:39 The basic idea 
39:17 ggdag
44:09 Exercise 1
50:33 Causal effects and backdoor paths
53:10 Exercise 2
1:01:19 Exercise 3
1:07:19 Resources: ggdag vignettes
1:08:43 Propensity Scores 
1:15:52 Exercise 1
1:20:10 Walk through
1:25:28 Propensity scores weighting 
1:36:55 Exercise 2
1:40:35 Walkthrough 
1:42:32 Propensity score diagnostic 
1:44:43 SMD in R
1:53:43 Outcome model
1:57:09 Exercise 
2:08:58 Walkthrough 
2:11:30 Thank you!


More Resources 

Main Site: https://www.r-consortium.org/ 
News: https://www.r-consortium.org/news 
Blog: https://www.r-consortium.org/news/blog 
Join: https://www.r-consortium.org/about/join 
Twitter: https://twitter.com/Rconsortium 
LinkedIn: https://www.linkedin.com/company/r-consortium/