causalweight: Estimation Methods for Causal Inference Based on Inverse Probability Weighting

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.

Package details

AuthorHugo Bodory [aut, cre] (<https://orcid.org/0000-0002-3645-1204>), Martin Huber [aut] (<https://orcid.org/0000-0002-8590-9402>)
MaintainerHugo Bodory <hugo.bodory@unisg.ch>
LicenseMIT + file LICENSE
Version1.0.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("causalweight")

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causalweight documentation built on April 16, 2021, 5:06 p.m.