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:

Reference manual:	AIPW.pdf
Vignettes:	Getting Started with AIPW

Downloads:

Package source:	AIPW_0.6.3.2.tar.gz
Windows binaries:	r-devel: AIPW_0.6.3.2.zip, r-release: AIPW_0.6.3.2.zip, r-oldrel: AIPW_0.6.3.2.zip
macOS binaries:	r-release (arm64): AIPW_0.6.3.2.tgz, r-oldrel (arm64): AIPW_0.6.3.2.tgz, r-release (x86_64): AIPW_0.6.3.2.tgz, r-oldrel (x86_64): AIPW_0.6.3.2.tgz

Reverse dependencies:

Reverse imports:

RobinCar

Linking:

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