Latent structureScale / measurement

Multi-group Generalizability Theory

Multi-group generalizability theory (MG G-theory) extends classical generalizability theory to estimate and compare variance components — attributable to persons, items, raters, occasions, and their interactions — simultaneously across two or more defined groups. It reveals whether a measurement procedure is equally reliable and generalizable for every group studied, supporting fair and equitable score interpretation.

Open in MethodMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. Brennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826
  2. Shavelson, R. J. & Webb, N. M. (1989). Generalizability theory: 1973–1988. British Journal of Mathematical and Statistical Psychology, 42(1), 3–27. DOI: 10.1111/j.2044-8317.1989.tb01112.x

Related methods

ScholarGateMulti-group Generalizability Theory (Multi-group Generalizability Theory). Retrieved 2026-06-04 from https://scholargate.app/en/psychometrics/multi-group-generalizability-theory