Salīdzināt metodes

	Ordinālā eksploratīvā faktoru analīze	Eksploratīvā faktoru analīze (EFA)
Nozare	Psihometrija	Statistika
Saime	Latent structure	Latent structure
Izcelsmes gads	1978–1984	—
Autors	Bengt Muthén	—
Tips	Latent variable / dimension reduction	Latent variable / dimension reduction
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.	Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299.
Citi nosaukumi	ordinal factor analysis, polychoric EFA, categorical EFA, EFA for ordinal data	common factor analysis, açımlayıcı faktör analizi, factor analysis
Saistītās	5	4
Kopsavilkums	Ordinal exploratory factor analysis discovers latent factors underlying a set of ordinal items — typically Likert scales — by computing polychoric correlations among the items and then applying a weighted least squares estimator. It avoids the distortions that arise when continuous EFA methods are naively applied to ordered categorical responses.	Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance.