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causalweight  

Estimation Methods for Causal Inference Based on Inverse Probability Weighting and Doubly Robust Estimation
View on CRAN: Click here


Download and install causalweight package within the R console
Install from CRAN:
install.packages("causalweight")

Install from Github:
library("remotes")
install_github("cran/causalweight")

Install by package version:
library("remotes")
install_version("causalweight", "1.1.4")



Attach the package and use:
library("causalweight")
Maintained by
Hugo Bodory
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-02-23
Latest Update: 2025-03-26
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.
How to cite:
Hugo Bodory (2018). causalweight: Estimation Methods for Causal Inference Based on Inverse Probability Weighting and Doubly Robust Estimation. R package version 1.1.4, https://cran.r-project.org/web/packages/causalweight. Accessed 15 Jul. 2026.
Previous versions and publish date:
(2026-07-09 07:24), 0.1.0 (2018-02-23 10:12), 0.1.1 (2018-08-01 12:40), 0.1.2 (2018-12-01 23:40), 0.1.3 (2019-12-05 17:00), 0.2.1 (2020-06-15 14:10), 1.0.0 (2020-12-02 16:50), 1.0.1 (2021-04-16 17:00), 1.0.2 (2021-07-08 11:30), 1.0.3 (2022-08-12 10:10), 1.0.4 (2023-05-04 16:40), 1.1.0 (2024-01-24 15:32), 1.1.1 (2024-07-23 15:40), 1.1.2 (2025-03-22 12:50), 1.1.3 (2025-03-26 09:30), 1.1.4 (2025-12-01 17:00)
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