# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "aiDIF" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'aiDIF: Differential Item Functioning for AI-Scored Assessments'
version: 0.1.0
doi: 10.32614/CRAN.package.aiDIF
abstract: 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.
authors:
- family-names: Hait
  given-names: Subir
  email: haitsubi@msu.edu
  orcid: https://orcid.org/0009-0004-9871-9677
repository: https://causalfragility-lab.r-universe.dev
repository-code: https://github.com/causalfragility-lab/aiDIF
commit: 9515141f1926b004aa6636f9fafafb8781fd19f8
url: https://github.com/causalfragility-lab/aiDIF
date-released: '2026-04-20'
contact:
- family-names: Hait
  given-names: Subir
  email: haitsubi@msu.edu
  orcid: https://orcid.org/0009-0004-9871-9677