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| Lý thuyết tổng quát hóa đa cấp× | Lý thuyết Khả năng Tổng quát (G-Theory)× | |
|---|---|---|
| Lĩnh vực | Trắc lượng tâm lý | Trắc lượng tâm lý |
| Họ | Latent structure | Latent structure |
| Năm ra đời≠ | 1990s–2000s | 1963–1972 |
| Người khởi xướng≠ | 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 |
| Loại≠ | Measurement / variance decomposition | Variance-components reliability model |
| Công trình gốc≠ | 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. link ↗ | Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley. link ↗ |
| Tên gọi khác≠ | multilevel G-theory, ML-GT, hierarchical generalizability theory, multilevel G-study | G-theory, G-study / D-study framework, variance components reliability |
| Liên quan | 4 | 4 |
| Tóm tắt≠ | 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. |
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