方法对比
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| 多群体拉斯奇模型× | 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≠ | 1960 (Rasch); 1980s–1990s (multi-group extensions) | 1971 |
| 提出者≠ | Georg Rasch (single-group); extended to multi-group applications by Fischer, Molenaar, and others | Karl Jöreskog |
| 类型≠ | Item response model / measurement invariance test | Measurement model / invariance test |
| 开创性文献≠ | Fischer, G. H. & Molenaar, I. W. (Eds.) (1995). Rasch Models: Foundations, Recent Developments, and Applications. Springer. ISBN: 978-0387944296 | 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 | MG-Rasch, Rasch measurement invariance, multi-group 1PL IRT, cross-group Rasch analysis | MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA |
| 相关 | 6 | 6 |
| 摘要≠ | The multi-group Rasch model fits the one-parameter logistic item response model simultaneously across two or more distinct groups, testing whether item difficulty parameters are invariant across groups. It is the primary psychometric tool for establishing that a scale measures the same latent trait with the same metric in each group, a prerequisite for meaningful score comparisons. | 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. |
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