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。
| 多层判别效度× | 多层测量不变性× | |
|---|---|---|
| 领域 | 心理测量学 | 心理测量学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 2005 | 2000s |
| 提出者≠ | Dyer, Hanges, & Hall; Chen, Sousa, & West | Muthén, Asparouhov, and colleagues |
| 类型≠ | Validity evaluation within multilevel CFA | Measurement model evaluation |
| 开创性文献≠ | Dyer, N. G., Hanges, P. J., & Hall, R. J. (2005). Applying multilevel confirmatory factor analysis techniques to the study of leadership. Leadership Quarterly, 16(1), 149–167. DOI ↗ | Muthén, B. O., & Asparouhov, T. (2009). Multilevel factor analysis of class and student achievement components. Journal of Educational and Behavioral Statistics, 34(2), 250–270. link ↗ |
| 别名 | multilevel DV, cross-level discriminant validity, hierarchical discriminant validity, ML-DV | MLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance |
| 相关≠ | 5 | 3 |
| 摘要≠ | Multilevel discriminant validity evaluates whether theoretically distinct constructs are empirically separable when data are nested within higher-level units such as teams, schools, or organizations. It extends single-level discriminant validity checks into a multilevel confirmatory factor analysis framework, verifying that constructs are distinguishable both within and between levels simultaneously. | Multilevel measurement invariance testing evaluates whether a latent construct is measured equivalently both within clusters (e.g., individuals within teams) and between clusters (e.g., team-level aggregates). It extends standard measurement invariance procedures to nested data structures commonly encountered in organisational, educational, and cross-cultural research. |
| ScholarGate数据集 ↗ |
|
|