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| 多群体普遍性理论× | 多群体测量不变性检验× | |
|---|---|---|
| 领域 | 心理测量学 | 心理测量学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 1963–2001 | 1971–1993 |
| 提出者≠ | Lee J. Cronbach and colleagues (Cronbach, Gleser, Nanda, Rajaratnam), extended to multi-group contexts by Brennan and others | Jöreskog, K. G. (1971); Meredith, W. (1993) |
| 类型≠ | Variance component / reliability generalization | Model comparison / hypothesis testing |
| 开创性文献≠ | Brennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826 | Vandenberg, R. J. & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. DOI ↗ |
| 别名 | MG G-theory, multi-group G-theory, generalizability theory across groups, cross-group G-study | measurement invariance, factorial invariance, cross-group invariance, MI testing |
| 相关 | 6 | 6 |
| 摘要≠ | Multi-group generalizability theory (MG G-theory) extends classical generalizability theory to estimate and compare variance components — attributable to persons, items, raters, occasions, and their interactions — simultaneously across two or more defined groups. It reveals whether a measurement procedure is equally reliable and generalizable for every group studied, supporting fair and equitable score interpretation. | Multi-group measurement invariance testing examines whether a latent construct is measured in the same way across two or more distinct groups — such as cultures, genders, or age cohorts. It is a prerequisite for meaningful group comparisons of latent means or relationships, ensuring that observed score differences reflect true differences rather than measurement artifacts. |
| ScholarGate数据集 ↗ |
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