Comparer des méthodes

	Fonctionnement Différentiel des Items Multiniveaux (DIF Multiniveaux)	Théorie de la réponse aux items (TRI)
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	2001	1952–1968
Auteur d'origine	Kamata (2001) and subsequent multilevel IRT/DIF literature	Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
Type	Bias detection / multilevel measurement model	Probabilistic measurement model
Source fondatrice	French, B. F., & Finch, W. H. (2008). Multigroup confirmatory factor analysis: Locating the invariant referent sets. Structural Equation Modeling: A Multidisciplinary Journal, 15(1), 96–113.	Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley.
Alias	multilevel DIF, hierarchical DIF analysis, cross-level DIF, ML-DIF	IRT, latent trait theory, item characteristic curve theory, modern test theory
Apparentées	5	5
Résumé	Multilevel DIF analysis detects whether individual test or survey items function differently across groups when respondents are clustered within higher-level units — such as students nested in schools, employees in organizations, or patients in clinics. By accounting for hierarchical data structure, it separates genuine item bias from artificial DIF signals caused by ignoring clustering.	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.