Latent structureScale / measurement

Multilevel Generalizability Theory

Multilevel generalizability theory extends classical G-theory to measurement designs where observations are nested within higher-level units — for example, items nested within raters, or students nested within classrooms. It decomposes score variance into components attributable to persons, facets, and their interactions across hierarchical levels, enabling precise estimation of measurement precision in complex, real-world assessment settings.

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Sources

  1. Briggs, D. C. & Wilson, M. (2003). An introduction to multidimensional measurement using Rasch models and generalizability theory. Journal of Applied Measurement, 4(1), 1–19. link
  2. Webb, N. M., Shavelson, R. J. & Haertel, E. H. (2006). Reliability coefficients and generalizability theory. Handbook of Statistics, 26, 81–124. DOI: 10.1016/S0169-7161(06)26004-8

Related methods

ScholarGateMultilevel Generalizability Theory (Multilevel Generalizability Theory). Retrieved 2026-06-04 from https://scholargate.app/en/psychometrics/multilevel-generalizability-theory