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AIPW: Augmented Inverse Probability Weighting
The 'AIPW' pacakge 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, In Press). AIPW: An R Package for Augmented Inverse Probability Weighted Estimation of Average Causal Effects. American Journal of Epidemiology". Visit: <https://yqzhong7.github.io/AIPW/> for more information.
| Version: |
0.6.3.2 |
| Depends: |
R (≥ 2.10) |
| Imports: |
stats, utils, R6, SuperLearner, ggplot2, future.apply, progressr, Rsolnp |
| Suggests: |
testthat (≥ 2.1.0), knitr, rmarkdown, covr, tmle |
| Published: |
2021-06-11 |
| 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 |
| In views: |
CausalInference |
| CRAN checks: |
AIPW results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
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https://CRAN.R-project.org/package=AIPW
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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