Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Modelul de Mixtură de Creștere (GMM)× | Analiza Factorială Exploratorie (EFA)× | |
|---|---|---|
| Domeniu | Statistică | Statistică |
| Familie | Latent structure | Latent structure |
| Anul apariției≠ | 1999 | — |
| Autorul original≠ | Bengt O. Muthén & Kerby Shedden | — |
| Tip≠ | Latent class / longitudinal growth model | Latent variable / dimension reduction |
| Sursa seminală≠ | Muthén, B. O. & Shedden, K. (1999). Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm. Biometrics, 55(2), 463–469. 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 ↗ |
| Denumiri alternative≠ | Büyüme Karışım Modeli (Growth Mixture Model — GMM), GMM, latent class growth analysis extension, mixture latent growth curve model | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| Înrudite≠ | 5 | 4 |
| Rezumat≠ | The Growth Mixture Model, introduced by Muthén and Shedden in 1999, is a longitudinal latent variable method that identifies distinct subpopulations — latent trajectory classes — each following its own growth curve over time. It extends the standard Latent Growth Curve (LGC) model by allowing the sample to be composed of an unknown mixture of classes with different intercepts, slopes, and variance structures. | 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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