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Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Analyse factorielle confirmatoire ordinale× | Analyse factorielle exploratoire (AFE)× | |
|---|---|---|
| Domaine≠ | Psychométrie | Statistique |
| Famille | Latent structure | Latent structure |
| Année d'origine≠ | 1984 | — |
| Auteur d'origine≠ | Bengt O. Muthén | — |
| Type≠ | Latent variable / structural | Latent variable / dimension reduction |
| Source fondatrice≠ | 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 ↗ | 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. DOI ↗ |
| Alias≠ | CFA for ordinal data, polychoric CFA, WLSMV CFA, categorical CFA | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| Apparentées≠ | 5 | 4 |
| Résumé≠ | 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. | 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. |
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