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.
Version: 1.1.3 Depends: R (≥ 3.5.0), ranger Imports: mvtnorm, np, LARF, hdm, SuperLearner, glmnet, xgboost, e1071, fastDummies, grf, checkmate, sandwich Published: 2025-03-26 DOI: 10.32614/CRAN.package.causalweight Author: Hugo Bodory [aut, cre], Martin Huber [aut], Jannis Kueck [aut] Maintainer: Hugo Bodory <hugo.bodory at unisg.ch> License: MIT + file LICENSE NeedsCompilation: no In views: CausalInference CRAN checks: causalweight results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=causalweight to link to this page.
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