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Эксплораторный факторный анализ (ЭФА)×Моделирование структурными уравнениями (SEM)×
ОбластьСтатистикаСтатистика
СемействоLatent structureLatent structure
Год появления1970
Автор методаKarl Jöreskog (LISREL framework, 1970s)
ТипLatent variable / dimension reductionLatent variable / causal modeling
Основополагающий источникFabrigar, 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
Другие названияcommon factor analysis, açımlayıcı faktör analizi, factor analysisYapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling
Связанные45
СводкаExploratory 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.
ScholarGateНабор данных
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ScholarGateСравнение методов: EFA · SEM. Получено 2026-06-15 из https://scholargate.app/ru/compare