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PSW
View on CRAN: Click
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Download and install PSW package within the R console
Install from CRAN:
install.packages("PSW")
Install from Github:
library("remotes")
install_github("cran/PSW") Install by package version:
library("remotes")
install_version("PSW", "1.1-3") Attach the package and use:
library("PSW")
Maintained by
Huzhang Mao
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-09-22
Latest Update: 2018-01-19
Description:
Provides propensity score weighting methods to control for confounding in causal inference with dichotomous treatments and continuous/binary outcomes. It includes the following functional modules: (1) visualization of the propensity score distribution in both treatment groups with mirror histogram, (2) covariate balance diagnosis, (3) propensity score model specification test, (4) weighted estimation of treatment effect, and (5) augmented estimation of treatment effect with outcome regression. The weighting methods include the inverse probability weight (IPW) for estimating the average treatment effect (ATE), the IPW for average treatment effect of the treated (ATT), the IPW for the average treatment effect of the controls (ATC), the matching weight (MW), the overlap weight (OVERLAP), and the trapezoidal weight (TRAPEZOIDAL). Sandwich variance estimation is provided to adjust for the sampling variability of the estimated propensity score. These methods are discussed by Hirano et al (2003) , Lunceford and Davidian (2004) , Li and Greene (2013) , and Li et al (2016) .
How to cite:
Huzhang Mao (2017). PSW: Propensity Score Weighting Methods for Dichotomous Treatments. R package version 1.1-3, https://cran.r-project.org/web/packages/PSW. Accessed 25 Jun. 2026.
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Complete documentation for PSW
Functions, R codes and Examples using
the PSW R package
Some associated functions: psw.aug . psw.balance . psw.mirror.hist . psw . psw.spec.test . psw.wt . test_data .
Some associated R codes: psw-internal.R . psw_aug.R . psw_balance.R . psw_main.R . psw_mirror_hist.R . psw_spec_test.R . psw_wt.R . test_data.R . Full PSW package functions and examples
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