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.

Open in MethodMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

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/en/psychometrics/robust-measurement-invariance