Comparer des méthodes

	Test d'invariance de mesure ordinale	Analyse factorielle confirmatoire ordinale
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1984–2011	1984
Auteur d'origine	Roger Millsap; Bengt Muthén	Bengt O. Muthén
Type	Multi-group model comparison	Latent variable / structural
Source fondatrice	Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936	Flora, D. B. & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9(4), 466–491.
Alias	ordinal MI, measurement invariance for ordinal data, ordinal CFA invariance, categorical measurement invariance	CFA for ordinal data, polychoric CFA, WLSMV CFA, categorical CFA
Apparentées	6	5
Résumé	Ordinal measurement invariance testing evaluates whether a multi-group confirmatory factor model holds equivalent measurement properties across groups when scale items are ordinal — such as Likert-type response scales. It uses polychoric correlations and categorical estimators (WLSMV/DWLS) rather than Pearson-based methods, correcting the systematic bias that arises when ordinal data are treated as continuous.	Ordinal confirmatory factor analysis (Ordinal CFA) tests a pre-specified factor structure when the observed indicators are ordinal — typically Likert-type survey items. By using polychoric correlations and robust estimators such as WLSMV, it avoids the bias that arises from treating categorical responses as continuous.