方法对比

	多层可推广性理论	概化理论（G-Theory）
领域	心理测量学	心理测量学
方法族	Latent structure	Latent structure
起源年份	1990s–2000s	1963–1972
提出者	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
类型	Measurement / variance decomposition	Variance-components reliability model
开创性文献	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.
别名	multilevel G-theory, ML-GT, hierarchical generalizability theory, multilevel G-study	G-theory, G-study / D-study framework, variance components reliability
相关	4	4
摘要	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.