Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Bifaktora modelis (vispārējie un specifiskie faktori)× | Eksploratīvā faktoru analīze (EFA)× | |
|---|---|---|
| Nozare≠ | Psihometrija | Statistika |
| Saime | Latent structure | Latent structure |
| Izcelsmes gads≠ | 1937 | — |
| Autors≠ | Holzinger & Swineford (1937); modern revival by Reise (2012) | — |
| Tips≠ | Confirmatory latent variable model | Latent variable / dimension reduction |
| Pirmavots≠ | Reise, S. P. (2012). The Rediscovery of Bifactor Measurement Models. Multivariate Behavioral Research, 47(5), 667–696. 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≠ | Bifaktör Modeli — Genel ve Spesifik Faktörler, hierarchical factor model, general-specific factor model, Schmid-Leiman model | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| Saistītās≠ | 6 | 4 |
| Kopsavilkums≠ | The bifactor measurement model specifies that every indicator loads simultaneously on a single general factor and on one of several specific (group) factors. Formally introduced by Holzinger and Swineford in 1937 and brought into mainstream psychometrics by Reise (2012), it is now the standard tool for evaluating whether a multidimensional scale can legitimately yield a single composite score. | 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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