Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Analyse factorielle exploratoire (AFE)× | Analyse Factorielle Confirmatoire (AFC)× | |
|---|---|---|
| Domaine≠ | Statistique | Psychométrie |
| Famille | Latent structure | Latent structure |
| Année d'origine≠ | — | 1969 |
| Auteur d'origine≠ | — | Karl Gustav Jöreskog |
| Type≠ | Latent variable / dimension reduction | Hypothesis-testing latent variable model |
| Source fondatrice≠ | 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 ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Alias≠ | common factor analysis, açımlayıcı faktör analizi, factor analysis | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Apparentées | 4 | 4 |
| Résumé≠ | 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. | Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing. |
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