Information on designing, organizing, and interpreting observational or quasi-randomized studies, in R and Python
See the Wiki for more information.
See the Notebooks directory for github-rendered Rmarkdown notebooks.
- https://kosukeimai.github.io/MatchIt/
- https://ngreifer.github.io/cobalt/
- https://zeligproject.org/
- https://microsoft.github.io/dowhy/
- https://books.ropensci.org/targets/
- https://humboldt-wi.github.io/blog/research/information_systems_1920/group5_causal_neural_networks/
- https://humboldt-wi.github.io/blog/research/applied_predictive_modeling_19/matching_methods/
- https://www.mostlyharmlesseconometrics.com/book-contents/
- https://www.econometrics-with-r.org/
- https://statlearning.com/
- http://www.stat.columbia.edu/~gelman/arm/chap9.pdf
- http://www.stat.columbia.edu/~gelman/arm/chap10.pdf
- https://mitpress.mit.edu/books/elements-causal-inference?source=post_page---------------------------
- https://cdn1.sph.harvard.edu/wp-content/uploads/sites/1268/2020/01/ci_hernanrobins_21jan20.pdf
- https://mixtape.scunning.com/index.html
- https://www.causalflows.com/