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| Computerized Adaptive Test Differential Item Functioning (CAT-DIF)× | Multi-Group Differential Item Functioning (MG-DIF)× | |
|---|---|---|
| Fachgebiet | Psychometrie | Psychometrie |
| Familie | Latent structure | Latent structure |
| Entstehungsjahr≠ | 1990s–2000s | 1980s-1990s |
| Urheber≠ | Wainer, Zwick, and colleagues in the CAT and DIF literatures | Shealy & Stout (SIBTEST framework); Lord (IRT-based DIF) |
| Typ≠ | Item bias detection in adaptive testing | Measurement bias detection |
| Wegweisende Quelle≠ | Zwick, R., Thayer, D. T., & Mazzeo, J. (1997). Describing and categorizing DIF in polytomous items. Journal of Educational Measurement, 34(4), 261–285. DOI ↗ | Millsap, R. E. (2012). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 |
| Aliasnamen | CAT DIF analysis, adaptive test DIF, DIF in computerized adaptive testing, CAT item bias detection | MG-DIF, multi-group DIF, differential item functioning across groups, multiple-group DIF analysis |
| Verwandt | 6 | 6 |
| Zusammenfassung≠ | CAT-DIF identifies items in a computerized adaptive test that behave differently across demographic or group subpopulations after controlling for overall ability. Because adaptive algorithms select items non-randomly based on each examinee's estimated proficiency, standard DIF detection methods require adjustment before they can be validly applied in this context. | Multi-group differential item functioning examines whether test or scale items function equivalently across three or more distinct groups — such as gender, ethnicity, or country — after matching respondents on the underlying trait being measured. Items that behave differently across groups threaten fair measurement and valid score comparisons. |
| ScholarGateDatensatz ↗ |
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