Methoden vergelijken

	Growth Mixture Model (GMM)	Exploratieve factoranalyse (EFA)
Vakgebied	Statistiek	Statistiek
Familie	Latent structure	Latent structure
Jaar van ontstaan	1999	—
Grondlegger	Bengt O. Muthén & Kerby Shedden	—
Type	Latent class / longitudinal growth model	Latent variable / dimension reduction
Oorspronkelijke bron	Muthén, B. O. & Shedden, K. (1999). Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm. Biometrics, 55(2), 463–469.	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.
Aliassen	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
Verwant	5	4
Samenvatting	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.