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