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。
| 多群体量表开发× | 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≠ | 1971 (multi-group CFA); 2000 (applied synthesis for scale development) | 1969 |
| 提出者≠ | Jöreskog, K. G. (multi-group SEM framework); systematised for scale development by Vandenberg & Lance (2000) | Karl Gustav Jöreskog |
| 类型≠ | Scale development / measurement model testing | Hypothesis-testing latent variable model |
| 开创性文献≠ | 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 ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| 别名 | MGSD, cross-group scale development, multi-sample scale development, comparative scale construction | CFA, confirmatory FA, measurement model, restricted factor analysis |
| 相关≠ | 6 | 4 |
| 摘要≠ | Multi-group scale development constructs and validates a measurement scale simultaneously across two or more distinct populations or groups. The approach integrates standard item generation and factor-analytic procedures with a systematic hierarchy of measurement invariance tests to ensure that the resulting scale measures the same construct in the same way in every target group. | 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 ↗ |
|
|