Package: aiDIF
Type: Package
Title: Differential Item Functioning for AI-Scored Assessments
Version: 0.3.0
Authors@R: 
    person("Subir", "Hait",
           email = "haitsubi@msu.edu",
           role = c("aut", "cre"),
           comment = c(ORCID = "0009-0004-9871-9677"))
Description: 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), cross-checked
    against the reference implementation in 'robustDIF', 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,
    including a bootstrap estimator of the cross-condition covariance that
    paired designs require, a one-call workflow from raw item scores
    through 'mirt' calibration, robust linking of the cross-condition
    contrast, bootstrap standard errors, multiplicity control, simulation
    of paired human and AI item scores, anchor weight diagnostics, and an
    AI-effect classification framework. Methods follow Halpin (2024)
    <doi:10.1007/s11336-024-09957-6>.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: Matrix, stats, graphics, utils, parallel
Suggests: mirt, robustDIF, testthat (>= 3.1.5), knitr, rmarkdown
Config/testthat/edition: 3
VignetteBuilder: knitr
URL: https://github.com/subirhait/aiDIF
BugReports: https://github.com/subirhait/aiDIF/issues
NeedsCompilation: no
Config/roxygen2/version: 8.1.1
Packaged: 2026-10-21 21:29:28 UTC; subir
Author: Subir Hait [aut, cre] (ORCID: <https://orcid.org/0009-0004-9871-9677>)
Maintainer: Subir Hait <haitsubi@msu.edu>
Repository: CRAN
Date/Publication: 2026-10-22 23:40:13 UTC
