What is PRIDIT? | The PRIDIT Methodology | Step 1: Calculate Ridit Scores | Step 2: Calculate PRIDIT Weights | Step 3: Calculate Final PRIDIT Scores | Package Functions | Basic Example | Using the Built-in Test Dataset | Interpreting PRIDIT Scores | Practical Applications | Quality Assessment | Variable Importance Analysis | Best Practices | Data Preparation | Interpretation Guidelines | Advanced Example: Longitudinal Analysis | Conclusion | References
Package: pridit 1.1.1
pridit: Composite Scoring via Principal Component Analysis of Ridit Scores
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.
Authors:
pridit_1.1.1.tar.gz
pridit_1.1.1.zip(r-4.7)pridit_1.1.1.zip(r-4.6)pridit_1.1.1.zip(r-4.5)
pridit_1.1.1.tgz(r-4.6-any)pridit_1.1.1.tgz(r-4.5-any)
pridit_1.1.1.tar.gz(r-4.7-any)pridit_1.1.1.tar.gz(r-4.6-any)
pridit_1.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
pridit/json (API)
| # Install 'pridit' in R: |
| install.packages('pridit', repos = c('https://rlieberthal.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rlieberthal/pridit/issues
Datasets:
- test - Test dataset for PRIDIT analysis
Last updated from:39f7296c59. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 148 | ||
| source / vignettes | OK | 175 | ||
| linux-release-x86_64 | OK | 147 | ||
| macos-release-arm64 | OK | 110 | ||
| macos-oldrel-arm64 | OK | 83 | ||
| windows-devel | OK | 106 | ||
| windows-release | OK | 89 | ||
| windows-oldrel | OK | 138 | ||
| wasm-release | OK | 115 |
Exports:priditpridit_bootpridit_longitudinalPRIDITscorePRIDITweightriditstep_pridit
Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecycleR6RColorBrewerrlangS7scalesvctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Plot a PRIDIT model | autoplot.pridit |
| Plot bootstrap confidence intervals for a PRIDIT model | autoplot.pridit_boot |
| Plot a longitudinal PRIDIT analysis | autoplot.pridit_longitudinal |
| Extract PRIDIT weights | coef.pridit |
| pridit: Principal Component Analysis Applied to Ridit Scoring | pridit-package pridit |
| Bootstrap confidence intervals for PRIDIT scores and weights | pridit_boot |
| Longitudinal PRIDIT analysis | pridit_longitudinal |
| Compute PRIDIT scores | PRIDITscore |
| Compute PRIDIT weights | PRIDITweight |
| Compute ridit scores | ridit |
| recipes step: PRIDIT composite score | step_pridit |
| Test dataset for PRIDIT analysis | test |
