Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Ordinālā eksploratīvā faktoru analīze× | Vienuma atbildes teorija (IRT)× | |
|---|---|---|
| Nozare | Psihometrija | Psihometrija |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1978–1984 | 1952–1968 |
| Autors≠ | Bengt Muthén | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Tips≠ | Latent variable / dimension reduction | 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. DOI ↗ | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| Citi nosaukumi | ordinal factor analysis, polychoric EFA, categorical EFA, EFA for ordinal data | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Saistītās | 5 | 5 |
| 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. | 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. |
| ScholarGateDatu kopa ↗ |
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