Model-Averaged Propensity Scores Selected by Prognostic-Score Balance R package psAve version 1.0.1 Constructs a model-averaged propensity score as a convex combination of candidate propensity score models, with mixing weights selected on a simplex grid to optimize covariate or prognostic-score balance, implementing the method of Kabata, Stuart and Shintani (2024) <doi:10.1186/s12874-024-02350-y>. Prognostic scores follow Hansen (2008) <doi:10.1093/biomet/asn004>: outcome models are fit on untreated units only. The resulting score is designed to be supplied directly to the matchit() function of 'MatchIt' as a distance measure or to the weightit() function of 'WeightIt' as a propensity score, with balance assessment via 'cobalt'. Software Depends: R (>= 4.1) Imports: cobalt (>= 4.6.0), stats, utils, graphics Suggests: MatchIt, WeightIt, SuperLearner, rpart, ranger, xgboost, survey, testthat (>= 3.0.0), knitr, rmarkdown Daijiro Kabata <daijiro.kabata@port.kobe-u.ac.jp> Comprehensive R Archive Network (CRAN) Daijiro Kabata [aut, cre, cph] GPL (>= 2) 2026-07-10 application/tgz https://CRAN.R-project.org/package=psAve doi:10.32614/CRAN.package.psAve