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| Multi-Group Differential Item Functioning (MG-DIF)× | Differenzielles Item-Funktionieren (DIF)× | |
|---|---|---|
| Fachgebiet | Psychometrie | Psychometrie |
| Familie | Latent structure | Latent structure |
| Entstehungsjahr≠ | 1980s-1990s | 1970s–1993 |
| Urheber≠ | Shealy & Stout (SIBTEST framework); Lord (IRT-based DIF) | William H. Angoff and colleagues (ETS); systematized by Holland & Wainer |
| Typ≠ | Measurement bias detection | Item-level bias detection |
| Wegweisende Quelle≠ | Millsap, R. E. (2012). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 | Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589 |
| Aliasnamen | MG-DIF, multi-group DIF, differential item functioning across groups, multiple-group DIF analysis | DIF, item bias analysis, measurement non-equivalence, item-level measurement bias |
| Verwandt≠ | 6 | 5 |
| Zusammenfassung≠ | 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. | Differential item functioning identifies test or survey items that behave differently for examinees from different groups — such as gender, ethnicity, or language background — after controlling for the underlying ability or trait being measured. DIF analysis is essential for fairness evaluation in educational testing and psychological scale development. |
| ScholarGateDatensatz ↗ |
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