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| 多层重测信度× | 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≠ | 1979 (ICC foundation); multilevel extension: 1990s–2000s | 1963–1972 |
| 提出者≠ | Shrout & Fleiss (ICC foundation); multilevel extension by Goldstein, Snijders, and others | Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam |
| 类型≠ | Reliability estimation under hierarchical data | Variance-components reliability model |
| 开创性文献≠ | Shrout, P. E. & Fleiss, J. L. (1979). Intraclass correlations: Uses in assessing rater reliability. Psychological Bulletin, 86(2), 420–428. DOI ↗ | 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 ↗ |
| 别名≠ | hierarchical test-retest reliability, multilevel ICC reliability, nested test-retest reliability, ML-TRT reliability | G-theory, G-study / D-study framework, variance components reliability |
| 相关≠ | 5 | 4 |
| 摘要≠ | Multilevel test-retest reliability estimates how consistently a measurement instrument produces the same scores across repeated administrations when observations are nested within higher-level units — such as patients within clinics or students within classrooms. It partitions total score variance across levels using intraclass correlation coefficients derived from multilevel models. | 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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