Salīdzināt metodes
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| Longitudinālā eksploratīvā faktoru analīze (Longitudinālā EFA)× | Eksploratīvā faktoru analīze (EFA)× | |
|---|---|---|
| Nozare≠ | Psihometrija | Statistika |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1970s–1983 | — |
| Autors≠ | John R. Nesselroade and colleagues (lifespan developmental tradition) | — |
| Tips≠ | Latent variable / dimension reduction across time | Latent variable / dimension reduction |
| Pirmavots≠ | Nesselroade, J. R. (1983). Temporal selection and factor invariance in the study of development and change. In P. B. Baltes & O. G. Brim (Eds.), Life-Span Development and Behavior (Vol. 5, pp. 59–87). Academic Press. link ↗ | 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≠ | LEFA, longitudinal factor analysis, repeated-measures EFA, panel EFA | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| Saistītās≠ | 6 | 4 |
| Kopsavilkums≠ | Longitudinal EFA applies exploratory factor analysis separately at each measurement occasion — or jointly across occasions — to discover whether the same latent factor structure emerges over time and whether factor loadings remain stable across waves. It is the foundational data-driven approach for examining structural change and continuity in panel and developmental research. | 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. |
| ScholarGateDatu kopa ↗ |
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