Comparer des méthodes

	Analyse factorielle exploratoire multi-groupes (AFE-MG)	Analyse Factorielle Confirmatoire (AFC)
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1981	1969
Auteur d'origine	Muthén & Christoffersson	Karl Gustav Jöreskog
Type	Latent variable / multi-group dimension reduction	Hypothesis-testing latent variable model
Source fondatrice	Muthén, B. & Christoffersson, A. (1981). Simultaneous factor analysis of dichotomous variables in several groups. Psychometrika, 46(4), 407–419.	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Alias	MGEFA, multi-sample exploratory factor analysis, simultaneous EFA across groups, exploratory factor analysis with multiple groups	CFA, confirmatory FA, measurement model, restricted factor analysis
Apparentées	6	4
Résumé	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.	Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing.