Σύγκριση μεθόδων

	Πολυτομική Διερευνητική Ανάλυση Παραγόντων	Θεωρία Απόκρισης Ερωτήσεων (IRT)
Πεδίο	Ψυχομετρία	Ψυχομετρία
Οικογένεια	Latent structure	Latent structure
Έτος προέλευσης	1978	1952–1968
Δημιουργός	Bengt Muthén	Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
Τύπος	Latent variable / dimension reduction	Probabilistic measurement model
Θεμελιώδης πηγή	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.	Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley.
Εναλλακτικές ονομασίες	EFA for ordered-categorical data, polychoric EFA, ordinal exploratory factor analysis, polytomous factor analysis	IRT, latent trait theory, item characteristic curve theory, modern test theory
Συναφείς	4	5
Σύνοψη	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.	Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale, yielding measurement that is sample-independent for items and test-independent for persons.