Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Apstiprinošā faktoru analīze (AFA)× | Eksploratīvā faktoru analīze (EFA)× | |
|---|---|---|
| Nozare≠ | Psihometrija | Statistika |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1969 | — |
| Autors≠ | Karl Gustav Jöreskog | — |
| Tips≠ | Hypothesis-testing latent variable model | Latent variable / dimension reduction |
| Pirmavots≠ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. 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 ↗ |
| Citi nosaukumi≠ | CFA, confirmatory FA, measurement model, restricted factor analysis | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| Saistītās | 4 | 4 |
| Kopsavilkums≠ | 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. | 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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