Estimating Propensity Scores (PS), PS-Based Weights, and Effects // 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.