Salīdzināt metodes

	Ordinal Confirmatory Factor Analysis	Vienuma atbildes teorija (IRT)
Nozare	Psihometrija	Psihometrija
Saime	Latent structure	Latent structure
Izcelsmes gads	1984	1952–1968
Autors	Bengt O. Muthén	Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
Tips	Latent variable / structural	Probabilistic measurement model
Pirmavots	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.
Citi nosaukumi	CFA for ordinal data, polychoric CFA, WLSMV CFA, categorical CFA	IRT, latent trait theory, item characteristic curve theory, modern test theory
Saistītās	5	5
Kopsavilkums	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.	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.