Comparer des méthodes

	Analyse factorielle confirmatoire multi-groupes (AFC-MG)	Analyse Factorielle Confirmatoire (AFC)
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1971	1969
Auteur d'origine	Karl Jöreskog	Karl Gustav Jöreskog
Type	Measurement model / invariance test	Hypothesis-testing latent variable model
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.	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Alias	MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA	CFA, confirmatory FA, measurement model, restricted factor analysis
Apparentées	6	4
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.	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.