Principal Stratification Analysis in R R package PStrata version 1.0.1 Estimating causal effects in the presence of post-treatment confounding using principal stratification. 'PStrata' allows for customized monotonicity assumptions and exclusion restriction assumptions, with automatic full Bayesian inference supported by 'Stan'. The main workflow is PStrataModel() to specify the model, fit() to run MCMC sampling, estimate() to extract potential outcomes, and contrast() to compute causal effects. Visualization tools are provided for diagnosis and interpretation. See Liu and Li (2023) <doi:10.48550/arXiv.2304.02740> for details. Software Depends: R (>= 3.5.0) Imports: ggplot2, rstan, lme4, reformulas, purrr, stringr, stats Suggests: R.rsp Bo Liu <bo.liu1997@gmail.com> Comprehensive R Archive Network (CRAN) Bo Liu [aut, cre], Fan Li [ctb] GPL (>= 2) 2026-05-15 application/tgz https://CRAN.R-project.org/package=PStrata doi:10.32614/CRAN.package.PStrata