AIPW: Augmented Inverse Probability Weighting
The 'AIPW' package implements the augmented inverse probability weighting, a doubly robust estimator, for average causal effect estimation with user-defined stacked machine learning algorithms. To cite the 'AIPW' package, please use: "Yongqi Zhong, Edward H. Kennedy, Lisa M. Bodnar, Ashley I. Naimi (2021). AIPW: An R Package for Augmented Inverse Probability Weighted Estimation of Average Causal Effects. American Journal of Epidemiology. <doi:10.1093/aje/kwab207>". Visit: <https://yqzhong7.github.io/AIPW/> for more information.
| Version: | 0.6.9.2 | 
| Depends: | R (≥ 2.10) | 
| Imports: | stats, utils, R6, SuperLearner, ggplot2, future.apply, progressr, Rsolnp | 
| Suggests: | testthat (≥ 2.1.0), knitr, rmarkdown, covr, tmle | 
| Published: | 2025-04-05 | 
| DOI: | 10.32614/CRAN.package.AIPW | 
| Author: | Yongqi Zhong  [aut, cre],
  Ashley Naimi  [aut],
  Gabriel Conzuelo [ctb],
  Edward Kennedy [ctb] | 
| Maintainer: | Yongqi Zhong  <yq.zhong7 at gmail.com> | 
| BugReports: | https://github.com/yqzhong7/AIPW/issues | 
| License: | GPL-3 | 
| URL: | https://github.com/yqzhong7/AIPW | 
| NeedsCompilation: | no | 
| Language: | es | 
| Citation: | AIPW citation info | 
| Materials: | README, NEWS | 
| In views: | CausalInference | 
| CRAN checks: | AIPW results | 
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