chenweichen / causal-inference-visual-guides

A collection of visual guides to help applied scientists learn causal inference.

Visual Guides for Causal Inference

A collection of visual guides designed to help applied scientists learn causal inference.

Current guides include:

1. Targeted Maximum Likelihood Estimation (TMLE), a doubly robust semiparametric estimation method commonly used for causal inference. The guide shows the steps for estimating the mean difference in outcomes, adjusted for confounders, for a binary outcome and binary treatment. A full tutorial with R code is available on my blog.

2. Superlearning (also known as stacking), an ensemble learning method recommended to use with TMLE. A full tutorial with R code is available on my blog.

3. Definitions of causal inference intervention types with examples using U.S. air pollution data and a corresponding blog post

Causal Inference Comics

Recently I've also been playing around with comics for causal inference concepts! Here's a few so far:

Citation

To cite this repository, please use:

Katherine Hoffman. (2020, November 27). hoffmakl/causal-inference-visual-guides: Visual Guides for Causal Inference (Version 1.01). Zenodo. http://doi.org/10.5281/zenodo.4293931

References

Laan, M. J., & Rose, S. (2011). Targeted learning: Causal inference for observational and experimental data. New York: Springer.