Latent structureScale / measurement

Robust Measurement Invariance Testing

Robust measurement invariance testing evaluates whether a psychometric instrument measures the same latent construct in the same way across groups when observed data violate multivariate normality. It adapts standard multi-group CFA sequences by replacing ordinary chi-square statistics with robust alternatives such as the Satorra-Bentler scaled statistic, yielding trustworthy conclusions about factor loadings, intercepts, and residual variances even with skewed or ordinal data.

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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: Applications for developmental research (pp. 399–419). Sage. link
  2. Millsap, R. E. (2011). Statistical approaches to measurement invariance. Routledge. ISBN: 978-0805864786

Related methods

ScholarGateRobust Measurement Invariance (Robust Measurement Invariance Testing). Retrieved 2026-06-04 from https://scholargate.app/tr/psychometrics/robust-measurement-invariance