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PSsurvival: Propensity Score Methods for Survival Analysis
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>.
Getting started
Browse package contents
Package details |
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| Author | Chengxin Yang [aut, cre], Chao Cheng [aut], Fan Li [aut], Fan Li [aut] |
| Maintainer | Chengxin Yang <chengxin.yang@duke.edu> |
| License | GPL (>= 2) |
| Version | 0.1.0 |
| URL | https://github.com/cxinyang/PSsurvival |
| Package repository | View on CRAN |
| Installation |
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