Comparer des méthodes

	Analyse factorielle confirmatoire polytomique	Analyse factorielle exploratoire polytomique
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1984	1978
Auteur d'origine	Bengt Muthen	Bengt Muthén
Type	Latent variable / confirmatory measurement model	Latent variable / dimension reduction
Source fondatrice	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.	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	CFA for ordered categories, ordinal CFA, categorical CFA, WLSMV-CFA	EFA for ordered-categorical data, polychoric EFA, ordinal exploratory factor analysis, polytomous factor analysis
Apparentées	5	4
Résumé	Polytomous confirmatory factor analysis (CFA) tests a pre-specified factor structure when items have three or more ordered response categories (e.g., Likert scales). By working with polychoric correlations and robust estimators such as WLSMV, it avoids the distortions that arise when ordered categorical data are treated as continuous.	Polytomous exploratory factor analysis extends standard EFA to ordered categorical (Likert-type) response data by replacing the Pearson correlation matrix with a polychoric correlation matrix. It recovers the latent continuous variable that each polytomous item is assumed to reflect, yielding more accurate factor loadings and better-defined factor structures than treating ordinal scores as if they were continuous.