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Robuste konfirmatorische Faktorenanalyse×Exploratorische Faktorenanalyse (EFA)×
FachgebietStatistikStatistik
FamilieLatent structureLatent structure
Entstehungsjahr1984–1994
UrheberSatorra & Bentler (robust SE/chi-square corrections); Browne (ADF estimator)
TypConfirmatory latent variable model with robust estimationLatent variable / dimension reduction
Wegweisende QuelleSatorra, A. & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variables analysis: Applications for developmental research (pp. 399–419). Sage. link ↗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 ↗
AliasnamenRobust CFA, CFA with robust standard errors, Satorra-Bentler CFA, non-normal CFAcommon factor analysis, açımlayıcı faktör analizi, factor analysis
Verwandt64
ZusammenfassungRobust confirmatory factor analysis fits a pre-specified factor structure to observed data while correcting standard errors and goodness-of-fit statistics for violations of multivariate normality. It is the preferred variant of CFA whenever Likert-type, skewed, or kurtotic indicators make the classical normal-theory estimator unreliable.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.
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ScholarGateMethoden vergleichen: Robust Confirmatory Factor Analysis · EFA. Abgerufen am 2026-06-15 von https://scholargate.app/de/compare