Latent structureMultivariate analysis

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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Sources

  1. 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
  2. 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

Related methods

Referenced by

ScholarGateRobust Structural Equation Modeling (Robust Structural Equation Modeling). Retrieved 2026-06-04 from https://scholargate.app/tr/statistics/robust-structural-equation-modeling