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PSsurvival  

Propensity Score Methods for Survival Analysis
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("PSsurvival", "0.2.1")



Attach the package and use:
library("PSsurvival")
Maintained by
Chengxin Yang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-12-09
Latest Update: 2025-12-09
Description:
Implements propensity score weighting methods for estimating counterfactual survival functions and marginal hazard ratios in observational studies with time-to-event outcomes. Supports binary and multiple treatment groups with average treatment effect on the combined full population (ATE), average treatment effect on the treated or target group (ATT), and overlap weighting estimands. Includes symmetric (Crump) and asymmetric (Sturmer) trimming options for extreme propensity scores. Variance estimation via analytical M-estimation or bootstrap. Methods based on Cheng et al. (2022) <doi:10.1093/aje/kwac043> and Li & Li (2019) <doi:10.1214/19-AOAS1282>.
How to cite:
Chengxin Yang (2025). PSsurvival: Propensity Score Methods for Survival Analysis. R package version 0.2.1, https://cran.r-project.org/web/packages/PSsurvival. Accessed 24 Oct. 2026.
Previous versions and publish date:
(2026-07-09 10:40), 0.1.0 (2025-12-09 08:40), 0.2.0 (2026-01-10 16:10)
Other packages that cited PSsurvival R package
View PSsurvival citation profile
Other R packages that PSsurvival depends, imports, suggests or enhances
Complete documentation for PSsurvival
Functions, R codes and Examples using the PSsurvival R package
Full PSsurvival package functions and examples
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