Composite Scoring via Principal Component Analysis of Ridit Scores R package pridit version 1.1.1 Implements 'PRIDIT' (Principal Component Analysis applied to 'RIDITs'), an unsupervised, nonparametric method for aggregating ordinal, categorical, and continuous indicators into a single interpretable composite score. Originally proposed by Brockett et al. (2002) <doi:10.1111/1539-6975.00027> for insurance fraud detection and extended to hospital quality measurement by Lieberthal (2008) <doi:10.1111/j.1475-6773.2007.00821.x> and Lieberthal and Comer (2013) <doi:10.1111/rmir.12009>. The package provides: (1) low-level functions ridit(), PRIDITweight(), and PRIDITscore(); (2) a unified pridit() entry point returning a classed object with print, summary, 'autoplot', and 'coef' methods; (3) pridit_boot() for bootstrap confidence intervals on scores and weights; (4) a step_pridit() recipe step for out-of-sample scoring within the 'tidymodels' framework; and (5) pridit_longitudinal() for panel data, computing cross-period stability of scores and weights. Software Depends: R (>= 4.0.0) Imports: ggplot2 (>= 3.4.0), rlang, stats, utils Suggests: generics, patchwork, recipes (>= 1.0.0), testthat (>= 3.0.0), knitr, rmarkdown Robert D. Lieberthal <rlieberthal@gmail.com> Comprehensive R Archive Network (CRAN) Robert D. Lieberthal [aut, cre] Apache License (>= 2) 2026-05-31 application/tgz https://CRAN.R-project.org/package=pridit doi:10.32614/CRAN.package.pridit