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| 概化理论（G-Theory）× | 多层可靠性分析× | |
|---|---|---|
| 领域 | 心理测量学 | 心理测量学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 1963–1972 | 2014 |
| 提出者≠ | Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam | Geldhof, Preacher & Zyphur |
| 类型≠ | Variance-components reliability model | Reliability estimation / psychometric modeling |
| 开创性文献≠ | 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 ↗ | Geldhof, G. J., Preacher, K. J., & Zyphur, M. J. (2014). Reliability estimation in a multilevel confirmatory factor analysis framework. Psychological Methods, 19(1), 72–91. DOI ↗ |
| 别名≠ | G-theory, G-study / D-study framework, variance components reliability | multilevel omega, within-group reliability, between-group reliability, hierarchical reliability |
| 相关≠ | 4 | 3 |
| 摘要≠ | 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. | Multilevel reliability analysis estimates the internal consistency of scale scores separately at the within-group (individual) and between-group (cluster) levels. It corrects the bias that arises when ordinary alpha or omega is applied to hierarchically nested data, such as employees within organizations or students within classrooms. |
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