swMATH ID: 35698
Software Authors: Hugo Bodory; Martin Huber
Description: R package causalweight: Causal Inference Based on Inverse Probability Weighting, Doubly Robust Estimation, and Double Machine Learning. Various estimators of causal effects based on inverse probability weighting, doubly robust estimation, and double machine learning. Specifically, the package includes methods for estimating average treatment effects, direct and indirect effects in causal mediation analysis, and dynamic treatment effects. The models refer to studies of Froelich (2007) <doi:10.1016/j.jeconom.2006.06.004>, Huber (2012) <doi:10.3102/1076998611411917>, Huber (2014) <doi:10.1080/07474938.2013.806197>, Huber (2014) <doi:10.1002/jae.2341>, Froelich and Huber (2017) <doi:10.1111/rssb.12232>, Hsu, Huber, Lee, and Lettry (2020) <doi:10.1002/jae.2765>, and others.
Homepage: https://cran.r-project.org/web/packages/causalweight/index.html
Source Code:  https://github.com/cran/causalweight
Dependencies: R
Related Software: R; PSweight; sbw; twang; PSW; ATE; WeightIt; optweight; CBPS; gbm; MICE; BART; tmle; SuperLearner; drtmle; EValue; episensr; optmatch; Matching; MatchIt
Cited in: 0 Publications