Porovnat metody

	Teorie zobecnitelnosti pro více skupin	Teorie zobecnitelnosti (G-teorie)
Obor	Psychometrika	Psychometrika
Rodina	Latent structure	Latent structure
Rok vzniku	1963–2001	1963–1972
Tvůrce	Lee J. Cronbach and colleagues (Cronbach, Gleser, Nanda, Rajaratnam), extended to multi-group contexts by Brennan and others	Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam
Typ	Variance component / reliability generalization	Variance-components reliability model
Původní zdroj	Brennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826	Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley.
Další názvy	MG G-theory, multi-group G-theory, generalizability theory across groups, cross-group G-study	G-theory, G-study / D-study framework, variance components reliability
Příbuzné	6	4
Shrnutí	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.	Generalizability Theory is a psychometric framework that decomposes observed score variance into multiple sources — persons, items, raters, occasions, and their interactions — using analysis of variance. It replaces the single reliability coefficient of classical test theory with a family of coefficients that tell researchers how well scores generalize across different measurement conditions.