手法を比較
選択した手法を並べて確認できます。異なる行はハイライト表示されます。
| 多レベル一般化理論× | 一般化可能性理論(G理論)× | |
|---|---|---|
| 分野 | 心理測定学 | 心理測定学 |
| 系統 | Latent structure | Latent structure |
| 提唱年≠ | 1990s–2000s | 1963–1972 |
| 提唱者≠ | 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 |
| 種類≠ | Measurement / variance decomposition | Variance-components reliability model |
| 原典≠ | 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 ↗ |
| 別名≠ | multilevel G-theory, ML-GT, hierarchical generalizability theory, multilevel G-study | G-theory, G-study / D-study framework, variance components reliability |
| 関連 | 4 | 4 |
| 概要≠ | 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. |
| ScholarGateデータセット ↗ |
|
|