Methoden vergelijken

	Polytome Analyse van Confirmatieve Factorstructuur	Polytome Verkennende Factoranalyse
Vakgebied	Psychometrie	Psychometrie
Familie	Latent structure	Latent structure
Jaar van ontstaan	1984	1978
Grondlegger	Bengt Muthen	Bengt Muthén
Type	Latent variable / confirmatory measurement model	Latent variable / dimension reduction
Oorspronkelijke bron	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.
Aliassen	CFA for ordered categories, ordinal CFA, categorical CFA, WLSMV-CFA	EFA for ordered-categorical data, polychoric EFA, ordinal exploratory factor analysis, polytomous factor analysis
Verwant	5	4
Samenvatting	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.