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AIPW  

Augmented Inverse Probability Weighting
View on CRAN: Click here


Download and install AIPW package within the R console
Install from CRAN:
install.packages("AIPW")

Install from Github:
library("remotes")
install_github("cran/AIPW")

Install by package version:
library("remotes")
install_version("AIPW", "0.6.3.2")



Attach the package and use:
library("AIPW")
Maintained by
Yongqi Zhong
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-06-11
Latest Update: 2021-06-11
Description:
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: for more information.
How to cite:
Yongqi Zhong (2021). AIPW: Augmented Inverse Probability Weighting. R package version 0.6.3.2, https://cran.r-project.org/web/packages/AIPW. Accessed 06 Nov. 2024.
Previous versions and publish date:
No previous versions
Other packages that cited AIPW R package
View AIPW citation profile
Other R packages that AIPW depends, imports, suggests or enhances
Complete documentation for AIPW
Functions, R codes and Examples using the AIPW R package
Some associated functions: AIPW . AIPW_base . AIPW_nuis . AIPW_tmle . aipw_wrapper . eager_sim_obs . eager_sim_rct . fit . plot.ip_weights . plot.p_score . stratified_fit . summary . 
Some associated R codes: AIPW.R . AIPW_base.R . AIPW_nuis.R . AIPW_tmle.R . aipw_wrapper.R . data.R . util.R . zzz.R .  Full AIPW package functions and examples
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