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Exploratorische Faktorenanalyse (EFA)×Strukturelle Gleichungsmodellierung (SEM)×
FachgebietStatistikStatistik
FamilieLatent structureLatent structure
Entstehungsjahr1970
UrheberKarl Jöreskog (LISREL framework, 1970s)
TypLatent variable / dimension reductionLatent variable / causal modeling
Wegweisende QuelleFabrigar, 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 ↗Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540
Aliasnamencommon factor analysis, açımlayıcı faktör analizi, factor analysisYapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling
Verwandt45
ZusammenfassungExploratory 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.Structural equation modeling is a multivariate statistical framework that simultaneously estimates a measurement model — relating observed indicators to latent constructs — and a structural model specifying directional or reciprocal relationships among those constructs. Rooted in the LISREL tradition developed by Karl Jöreskog in the 1970s, SEM is the standard tool for testing complex theoretical models in the social, behavioural, and management sciences.
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ScholarGateMethoden vergleichen: EFA · SEM. Abgerufen am 2026-06-15 von https://scholargate.app/de/compare