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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 |
| 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 |
| In views: |
CausalInference |
| CRAN checks: |
AIPW results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=AIPW
to link to this page.
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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