방법 비교

	성장 혼합 모형 (Growth Mixture Model, GMM)	탐색적 요인 분석 (EFA)
분야	통계학	통계학
계열	Latent structure	Latent structure
기원 연도	1999	—
창시자	Bengt O. Muthén & Kerby Shedden	—
유형	Latent class / longitudinal growth model	Latent variable / dimension reduction
원전	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.
별칭	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
관련	5	4
요약	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.