aiDIF: Differential Item Functioning for AI-Scored Assessments
Detects and quantifies differential item functioning (DIF) in AI-scored educational and psychological assessments. Provides a fully self-contained robust DIF engine (M-estimation via iteratively re-weighted least squares with the bi-square loss) alongside the novel Differential AI Scoring Bias (DASB) test, which detects item-level scoring shifts that differ across subgroups when comparing human and AI scoring conditions. Includes simulation utilities, anchor weight diagnostics, and an AI-effect classification framework.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Matrix, stats, graphics |
| Suggests: | mirt, testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: | 2026-04-21 |
| DOI: | 10.32614/CRAN.package.aiDIF (may not be active yet) |
| Author: | Subir Hait  [aut,
cre] |
| Maintainer: | Subir Hait <haitsubi at msu.edu> |
| BugReports: | https://github.com/causalfragility-lab/aiDIF/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/causalfragility-lab/aiDIF |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | aiDIF results |
Documentation:
| Reference manual: | aiDIF.html , aiDIF.pdf |
| Vignettes: |
Introduction to aiDIF (source, R code) |
Downloads:
| Package source: | aiDIF_0.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available |
Linking:
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