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。
| 多组探索性因子分析 (MGEFA)× | 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≠ | 1981 | 1969 |
| 提出者≠ | Muthén & Christoffersson | Karl Gustav Jöreskog |
| 类型≠ | Latent variable / multi-group dimension reduction | Hypothesis-testing latent variable model |
| 开创性文献≠ | Muthén, B. & Christoffersson, A. (1981). Simultaneous factor analysis of dichotomous variables in several groups. Psychometrika, 46(4), 407–419. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| 别名 | MGEFA, multi-sample exploratory factor analysis, simultaneous EFA across groups, exploratory factor analysis with multiple groups | CFA, confirmatory FA, measurement model, restricted factor analysis |
| 相关≠ | 6 | 4 |
| 摘要≠ | Multi-group exploratory factor analysis estimates the latent factor structure of a set of items separately within each of two or more groups and then examines whether the discovered structures are consistent across groups. It is used to explore dimensionality before imposing invariance constraints, and to diagnose group-specific factor patterns that would invalidate cross-group comparisons. | 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 ↗ |
|
|