方法对比
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| 多群体量表开发× | 探索性因子分析（EFA）× | |
|---|---|---|
| 领域≠ | 心理测量学 | 统计学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 1971 (multi-group CFA); 2000 (applied synthesis for scale development) | — |
| 提出者≠ | Jöreskog, K. G. (multi-group SEM framework); systematised for scale development by Vandenberg & Lance (2000) | — |
| 类型≠ | Scale development / measurement model testing | Latent variable / dimension reduction |
| 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 ↗ | Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. DOI ↗ |
| 别名≠ | MGSD, cross-group scale development, multi-sample scale development, comparative scale construction | common factor analysis, açımlayıcı faktör analizi, 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. | Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance. |
| ScholarGate数据集 ↗ |
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