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	Wielopoziomowa teoria generalizacji	Teoria generalizowalności (G-Theory)
Dziedzina	Psychometria	Psychometria
Rodzina	Latent structure	Latent structure
Rok powstania	1990s–2000s	1963–1972
Twórca	Brennan, R. L. and Shavelson, R. J. (extensions of Cronbach et al. G-theory to multilevel designs)	Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam
Typ	Measurement / variance decomposition	Variance-components reliability model
Źródło pierwotne	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.	Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley.
Inne nazwy	multilevel G-theory, ML-GT, hierarchical generalizability theory, multilevel G-study	G-theory, G-study / D-study framework, variance components reliability
Pokrewne	4	4
Podsumowanie	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.	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.