Comparer des méthodes

	Analyse factorielle confirmatoire multi-groupes (AFC-MG)	Fonctionnement différentiel des items (FDI)
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1971	1970s–1993
Auteur d'origine	Karl Jöreskog	William H. Angoff and colleagues (ETS); systematized by Holland & Wainer
Type	Measurement model / invariance test	Item-level bias detection
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.	Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589
Alias	MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA	DIF, item bias analysis, measurement non-equivalence, item-level measurement bias
Apparentées	6	5
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.	Differential item functioning identifies test or survey items that behave differently for examinees from different groups — such as gender, ethnicity, or language background — after controlling for the underlying ability or trait being measured. DIF analysis is essential for fairness evaluation in educational testing and psychological scale development.