方法对比
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| 纵向探索性因子分析 (Longitudinal EFA)× | 多层探索性因子分析 (ML-EFA)× | |
|---|---|---|
| 领域 | 心理测量学 | 心理测量学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 1970s–1983 | 1994 |
| 提出者≠ | John R. Nesselroade and colleagues (lifespan developmental tradition) | Bengt O. Muthén |
| 类型≠ | Latent variable / dimension reduction across time | Latent variable / multilevel dimension reduction |
| 开创性文献≠ | Nesselroade, J. R. (1983). Temporal selection and factor invariance in the study of development and change. In P. B. Baltes & O. G. Brim (Eds.), Life-Span Development and Behavior (Vol. 5, pp. 59–87). Academic Press. link ↗ | Muthén, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods & Research, 22(3), 376–398. DOI ↗ |
| 别名 | LEFA, longitudinal factor analysis, repeated-measures EFA, panel EFA | ML-EFA, multilevel factor analysis, two-level exploratory factor analysis, hierarchical exploratory factor analysis |
| 相关≠ | 6 | 3 |
| 摘要≠ | Longitudinal EFA applies exploratory factor analysis separately at each measurement occasion — or jointly across occasions — to discover whether the same latent factor structure emerges over time and whether factor loadings remain stable across waves. It is the foundational data-driven approach for examining structural change and continuity in panel and developmental research. | Multilevel exploratory factor analysis uncovers latent factor structures simultaneously at two or more levels of a data hierarchy — for example, both within individuals and between groups — without imposing a fixed structure in advance. It is essential whenever survey or test items are collected from respondents nested inside classrooms, organisations, or clinics. |
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