方法对比
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| 多层重测信度× | 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≠ | 1979 (ICC foundation); multilevel extension: 1990s–2000s | 1969 |
| 提出者≠ | Shrout & Fleiss (ICC foundation); multilevel extension by Goldstein, Snijders, and others | Karl Gustav Jöreskog |
| 类型≠ | Reliability estimation under hierarchical data | Hypothesis-testing latent variable 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 ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| 别名 | hierarchical test-retest reliability, multilevel ICC reliability, nested test-retest reliability, ML-TRT reliability | CFA, confirmatory FA, measurement model, restricted factor analysis |
| 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. | 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. |
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