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| 多群体收敛效度× | 多组验证性因子分析 (MG-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 / 2000 | 1971 |
| 提出者≠ | Fornell & Larcker (convergent validity criteria); Vandenberg & Lance (multi-group extension) | Karl Jöreskog |
| 类型≠ | Validity assessment procedure | Measurement model / invariance test |
| 开创性文献≠ | Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. DOI ↗ | 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 ↗ |
| 别名 | cross-group convergent validity, multi-sample convergent validity, MGCFA convergent validity, AVE across groups | MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA |
| 相关 | 6 | 6 |
| 摘要≠ | Multi-group convergent validity examines whether items purported to measure the same latent construct relate strongly to that construct consistently across distinct subgroups such as demographic categories, cultures, or experimental conditions. It extends single-sample convergent validity checks into a comparative multi-group confirmatory factor analysis framework. | Multi-group confirmatory factor analysis tests whether a measurement model holds equivalently across two or more groups — such as cultures, genders, or time points. By imposing increasingly stringent equality constraints and comparing model fit, it determines whether comparisons of latent mean scores are justified. |
| ScholarGate数据集 ↗ |
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