Comparer des méthodes

	Fonctionnement différentiel des items multi-groupes (FDIM)	Analyse factorielle confirmatoire multi-groupes (AFC-MG)
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1980s-1990s	1971
Auteur d'origine	Shealy & Stout (SIBTEST framework); Lord (IRT-based DIF)	Karl Jöreskog
Type	Measurement bias detection	Measurement model / invariance test
Source fondatrice	Millsap, R. E. (2012). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936	Vandenberg, R. J. & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70.
Alias	MG-DIF, multi-group DIF, differential item functioning across groups, multiple-group DIF analysis	MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA
Apparentées	6	6
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.	Multi-group confirmatory factor analysis tests whether a measurement model holds equivalently across two or more groups — such as cultures, genders, or time points. By imposing increasingly stringent equality constraints and comparing model fit, it determines whether comparisons of latent mean scores are justified.