Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Fonctionnement différentiel des items multi-groupes (FDIM)× | Théorie de la réponse aux items (TRI)× | |
|---|---|---|
| Domaine | Psychométrie | Psychométrie |
| Famille | Latent structure | Latent structure |
| Année d'origine≠ | 1980s-1990s | 1952–1968 |
| Auteur d'origine≠ | Shealy & Stout (SIBTEST framework); Lord (IRT-based DIF) | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Type≠ | Measurement bias detection | Probabilistic measurement model |
| Source fondatrice≠ | Millsap, R. E. (2012). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| Alias | MG-DIF, multi-group DIF, differential item functioning across groups, multiple-group DIF analysis | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Apparentées≠ | 6 | 5 |
| Résumé≠ | 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. | Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale, yielding measurement that is sample-independent for items and test-independent for persons. |
| ScholarGateJeu de données ↗ |
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