ScholarGate
Assistent

Sammenlign metoder

Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.

Vekstblandingsmodell (GMM)×Eksplorerende faktoranalyse (EFA)×
FagfeltStatistikkStatistikk
FamilieLatent structureLatent structure
Opprinnelsesår1999
OpphavspersonBengt O. Muthén & Kerby Shedden
TypeLatent class / longitudinal growth modelLatent variable / dimension reduction
Opprinnelig kildeMuthén, 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 ↗
AliasBüyüme Karışım Modeli (Growth Mixture Model — GMM), GMM, latent class growth analysis extension, mixture latent growth curve modelcommon factor analysis, açımlayıcı faktör analizi, factor analysis
Relaterte54
SammendragThe 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.
ScholarGateDatasett
  1. v1
  2. 1 Kilder
  3. PUBLISHED
  1. v2
  2. 2 Kilder
  3. PUBLISHED

Gå til søk Last ned lysbilder

ScholarGateSammenlign metoder: GMM · EFA. Hentet 2026-06-17 fra https://scholargate.app/no/compare