Robust Structural Equation Modeling
Robust structural equation modeling (Robust SEM) applies the full SEM framework — simultaneous estimation of measurement and structural relations among latent variables — while using corrected test statistics and sandwich standard errors that remain valid when observed data depart from multivariate normality. The Satorra-Bentler scaled chi-square is the most widely used correction.
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Avoti
- Satorra, 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 (pp. 399–419). Sage. link ↗
- Yuan, K.-H. & Bentler, P. M. (1998). Normal theory based test statistics in structural equation modelling. British Journal of Mathematical and Statistical Psychology, 51(2), 289–309. DOI: 10.1111/j.2044-8317.1998.tb00682.x ↗
Kā citēt šo lapu
ScholarGate. (2026, June 3). Robust Structural Equation Modeling. ScholarGate. https://scholargate.app/lv/statistics/robust-structural-equation-modeling
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Apstiprinošā faktoru analīze (AFA)Psihometrija↔ compare
- Ceļu analīzeStatistika↔ compare
- Robustā robustā faktoru analīzeStatistika↔ compare
- Robust Path AnalysisStatistika↔ compare
- Modelēšana ar strukturālām vienādojumiemPētniecības statistika↔ compare
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