Latent structureScale / measurement

Robust Exploratory Factor Analysis

Robust exploratory factor analysis discovers the latent factor structure of a set of items using estimation methods that are resistant to outliers and violations of multivariate normality. It applies the same measurement model as standard EFA but replaces classical covariance estimation with robust counterparts — such as minimum covariance determinant or iteratively reweighted least squares — so that a small fraction of atypical cases cannot distort the recovered factor loadings.

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Sources

  1. Yuan, K.-H., & Bentler, P. M. (2000). Robust mean and covariance structure analysis through iteratively reweighted least squares. Psychometrika, 65(1), 43–58. DOI: 10.1007/BF02294180
  2. Pison, G., Rousseeuw, P. J., Filzmoser, P., & Croux, C. (2003). Robust factor analysis. Journal of Multivariate Analysis, 84(1), 145–172. DOI: 10.1016/S0047-259X(02)00007-6

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ScholarGateRobust Exploratory Factor Analysis (Robust Exploratory Factor Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/psychometrics/robust-exploratory-factor-analysis