方法对比
并排查看您选择的方法;存在差异的行会高亮显示。
| 概化理论(G-Theory)× | 验证性因子分析(CFA)× | |
|---|---|---|
| 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 | 1969 |
| 提出者≠ | Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam | Karl Gustav Jöreskog |
| 类型≠ | Variance-components reliability model | Hypothesis-testing latent variable model |
| 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 ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| 别名≠ | G-theory, G-study / D-study framework, variance components reliability | CFA, confirmatory FA, measurement model, restricted factor analysis |
| 相关 | 4 | 4 |
| 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. | Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing. |
| ScholarGate数据集 ↗ |
|
|