Comparer des méthodes

	Analyse factorielle confirmatoire multi-groupes (AFC-MG)	Analyse factorielle exploratoire multi-groupes (AFE-MG)
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1971	1981
Auteur d'origine	Karl Jöreskog	Muthén & Christoffersson
Type	Measurement model / invariance test	Latent variable / multi-group dimension reduction
Source fondatrice	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.	Muthén, B. & Christoffersson, A. (1981). Simultaneous factor analysis of dichotomous variables in several groups. Psychometrika, 46(4), 407–419.
Alias	MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA	MGEFA, multi-sample exploratory factor analysis, simultaneous EFA across groups, exploratory factor analysis with multiple groups
Apparentées	6	6
Résumé	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.	Multi-group exploratory factor analysis estimates the latent factor structure of a set of items separately within each of two or more groups and then examines whether the discovered structures are consistent across groups. It is used to explore dimensionality before imposing invariance constraints, and to diagnose group-specific factor patterns that would invalidate cross-group comparisons.