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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 Differential AI Scoring Bias (DASB) test, which detects item-level scoring shifts that differ across subgroups when comparing human and AI scoring conditions. Supports independent and paired scoring designs, robust linking of the cross-condition contrast, multiplicity control, conversion of fitted 'mirt' models to package inputs, simulation utilities, anchor weight diagnostics, and an AI-effect classification framework. Methods follow Halpin (2024) <doi:10.1007/s11336-024-09957-6>.
| Version: | 0.2.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Matrix, stats, graphics, utils |
| Suggests: | mirt, testthat (≥ 3.1.5), knitr, rmarkdown |
| Published: | 2026-09-05 |
| DOI: | 10.32614/CRAN.package.aiDIF |
| Author: | Subir Hait |
| 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 |
| Citation: | aiDIF citation info |
| Materials: | README, NEWS |
| CRAN checks: | aiDIF results |
| Reference manual: | aiDIF.html , aiDIF.pdf |
| Vignettes: |
Introduction to aiDIF (source, R code) |
| Package source: | aiDIF_0.2.0.tar.gz |
| Windows binaries: | r-devel: aiDIF_0.2.0.zip, r-release: aiDIF_0.2.0.zip, r-oldrel: aiDIF_0.2.0.zip |
| macOS binaries: | r-release (arm64): aiDIF_0.1.0.tgz, r-oldrel (arm64): aiDIF_0.2.0.tgz, r-release (x86_64): aiDIF_0.2.0.tgz, r-oldrel (x86_64): aiDIF_0.2.0.tgz |
| Old sources: | aiDIF archive |
| Reverse suggests: | aiEvalR |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.