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 | 
Documentation:
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