<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>cxinyang.r-universe.dev</title><link>https://cxinyang.r-universe.dev</link><description>Recent package updates in cxinyang</description><generator>R-universe</generator><image><url>https://github.com/cxinyang.png</url><title>R packages by cxinyang</title><link>https://cxinyang.r-universe.dev</link></image><lastBuildDate>Sat, 10 Jan 2026 03:58:53 GMT</lastBuildDate><item><title>[cxinyang] PSsurvival 0.2.0</title><author>chengxin.yang@duke.edu (Chengxin Yang)</author><description>Implements propensity score weighting methods for
estimating counterfactual survival functions, marginal hazard
ratios, and weighted Kaplan-Meier and cumulative risk curves in
observational studies with time-to-event outcomes. Supports
binary and multiple treatment groups with inverse probability
of treatment weighting (IPW), overlap weighting (OW), and
average treatment effect on the treated (ATT). Includes
symmetric trimming (Crump extension) for extreme propensity
scores. Variance estimation via analytical M-estimation or
bootstrap. Methods based on Li et al. (2018)
&lt;doi:10.1080/01621459.2016.1260466&gt;, Li &amp; Li (2019)
&lt;doi:10.1214/19-AOAS1282&gt;, and Cheng et al. (2022)
&lt;doi:10.1093/aje/kwac043&gt;.</description><link>https://github.com/r-universe/cxinyang/actions/runs/27814494843</link><pubDate>Sat, 10 Jan 2026 03:58:53 GMT</pubDate><r:package>PSsurvival</r:package><r:version>0.2.0</r:version><r:status>success</r:status><r:repository>https://cxinyang.r-universe.dev</r:repository><r:upstream>https://github.com/cxinyang/pssurvival</r:upstream><r:article><r:source>PSsurvival-tutorial.Rmd</r:source><r:filename>PSsurvival-tutorial.html</r:filename><r:title>PSsurvival: Propensity Score Weighting for Survival Analysis</r:title><r:created>2025-11-24 22:33:51</r:created><r:modified>2026-01-10 03:58:53</r:modified></r:article></item></channel></rss>