Estimating Propensity Scores (PS), PS-Based Weights, and Effects R package rwetools version 0.4.0 Toolbox that provides a streamlined, end-to-end workflow for propensity score analysis in generating real-world evidence from real-world data. The package covers the full analytic pipeline - from estimating propensity scores via logistic regression, to calculating weights or creating a matched cohort, to generating publication-ready Table 1s with standardized mean differences and weighted balance diagnostics. It also estimates incidence rates, hazard ratios, risk ratios, and risk differences with support for stratified and direct-standardized analyses. All core functions produce formatted 'Excel' reports with embedded 'README' documentation, making results immediately shareable with collaborators and stakeholders. Methods are based on Rosenbaum and Rubin (1983) <doi:10.1093/biomet/70.1.41>, Austin (2011) <doi:10.1080/00273171.2011.568786>, and Desai et al. (2017) <doi:10.1097/EDE.0000000000000595>. Software Depends: R (>= 3.5.0) Imports: stats, utils, parallel, survival, survey Suggests: openxlsx, ggplot2, MatchIt, testthat (>= 3.0.0) Hanseul Cho <hanseul0618@gmail.com> Comprehensive R Archive Network (CRAN) Hanseul Cho [aut, cre], Georg Hahn [aut], Janinne Ortega-Montiel [aut], Julie Paik [aut], Elisabetta Patorno [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=rwetools/LICENSE) 2026-08-01 application/tgz https://CRAN.R-project.org/package=rwetools doi:10.32614/CRAN.package.rwetools en-US