causalweight 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