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  "Description": "Implements 'PRIDIT' (Principal Component Analysis applied\nto 'RIDITs'), an unsupervised, nonparametric method for\naggregating ordinal, categorical, and continuous indicators\ninto a single interpretable composite score. Originally\nproposed by Brockett et al. (2002)\n<doi:10.1111/1539-6975.00027> for insurance fraud detection and\nextended to hospital quality measurement by Lieberthal (2008)\n<doi:10.1111/j.1475-6773.2007.00821.x> and Lieberthal and Comer\n(2013) <doi:10.1111/rmir.12009>. The package provides: (1)\nlow-level functions ridit(), PRIDITweight(), and PRIDITscore();\n(2) a unified pridit() entry point returning a classed object\nwith print, summary, 'autoplot', and 'coef' methods; (3)\npridit_boot() for bootstrap confidence intervals on scores and\nweights; (4) a step_pridit() recipe step for out-of-sample\nscoring within the 'tidymodels' framework; and (5)\npridit_longitudinal() for panel data, computing cross-period\nstability of scores and weights.",
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