Package: causalweight Title: Estimation Methods for Causal Inference Based on Inverse Probability Weighting Version: 1.1.0 Authors@R: c(person(given = "Hugo", family = "Bodory", role = c("aut", "cre"), email = "hugo.bodory@unisg.ch", comment = c(ORCID = "0000-0002-3645-1204")), person(given = "Martin", family = "Huber", role = "aut", email = "martin.huber@unifr.ch", comment = c(ORCID = "0000-0002-8590-9402")), person(given = "Jannis", family = "Kueck", role = "aut", email = "jannis.kueck@uni-hamburg.de", comment = c(ORCID = "0000-0003-4367-0285"))) Maintainer: Hugo Bodory Description: 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) , Huber (2012) , Huber (2014) , Huber (2014) , Froelich and Huber (2017) , Hsu, Huber, Lee, and Lettry (2020) , and others. License: MIT + file LICENSE Encoding: UTF-8 LazyData: true RoxygenNote: 7.2.3 Depends: R (>= 3.5.0), ranger Imports: mvtnorm, np, LARF, hdm, SuperLearner, glmnet, xgboost, e1071, fastDummies, grf, checkmate NeedsCompilation: no Packaged: 2024-01-24 14:02:52 UTC; HBodory Author: Hugo Bodory [aut, cre] (), Martin Huber [aut] (), Jannis Kueck [aut] () Repository: CRAN Date/Publication: 2024-01-24 14:32:55 UTC