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.
- Version1.1.1
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- Last release07/23/2024
Documentation
Team
Hugo Bodory
Martin Huber
Jannis Kueck
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- Depends1 package
- Imports12 packages