Using Interpretable Machine Learning for Differential Item Functioning Detection in Psychometric Tests

URN to cite this document:: urn:nbn:de:bvb:355-epub-582858
DOI to cite this document:: 10.5283/epub.58285

Kraus, Elisabeth Barbara ; Wild, Johannes

; Hilbert, Sven

License: Creative Commons Attribution Non-commercial 4.0
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Date of publication of this fulltext: 17 May 2024 11:55

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Abstract

This study presents a novel method to investigate test fairness and differential item functioning combining psychometrics and machine learning. Test unfairness manifests itself in systematic and demographically imbalanced influences of confounding constructs on residual variances in psychometric modeling. Our method aims to account for resulting complex relationships between response patterns and ...