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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.

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Taksonoomiline meetodikirje · latent-structure / psychometrics

Brennan, R. L. (2001). Generalizability Theory. Springer. · ISBN 978-0387952826
Shavelson, R. J. & Webb, N. M. (1989). Generalizability theory: 1973–1988. British Journal of Mathematical and Statistical Psychology, 42(1), 3–27. · DOI 10.1037/0003-066x.44.6.922

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Taxonomic bucketGeneralizability Theorymachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMulti-group confirmatory factor analysismachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMulti-group Cronbach's alphamachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMulti-group measurement invariancemachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMulti-group Rasch modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMulti-group Reliability Analysismachine-suggested · Relational suggestion, not evidence.