Package: causalweight
Type: Package
Title: Causal Inference Based on Inverse Probability Weighting, Doubly
        Robust Estimation, and Double Machine Learning
Version: 0.2.1
Author: Hugo Bodory and Martin Huber
Maintainer: Hugo Bodory <hugo.bodory@unifr.ch>
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) <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.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Depends: R (>= 3.5.0)
Imports: mvtnorm, np, LARF, hdm, SuperLearner, glmnet, ranger, xgboost,
        e1071
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-06-15 09:03:18 UTC; HBodory
Repository: CRAN
Date/Publication: 2020-06-15 12:10:11 UTC
