Latent structureScale / measurement

Multilevel Exploratory Factor Analysis (ML-EFA)

Multilevel exploratory factor analysis uncovers latent factor structures simultaneously at two or more levels of a data hierarchy — for example, both within individuals and between groups — without imposing a fixed structure in advance. It is essential whenever survey or test items are collected from respondents nested inside classrooms, organisations, or clinics.

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Sources

  1. Muthén, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods & Research, 22(3), 376–398. DOI: 10.1177/0049124194022003006
  2. Ryu, E. & West, S. G. (2009). Level-specific evaluation of model fit in multilevel structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 16(4), 583–601. DOI: 10.1080/10705510903203466

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Referenced by

ScholarGateMultilevel EFA (Multilevel Exploratory Factor Analysis). Retrieved 2026-06-04 from https://scholargate.app/tr/psychometrics/multilevel-exploratory-factor-analysis