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。
| 多组验证性因子分析 (MG-CFA)× | 差异项目功能 (DIF)× | |
|---|---|---|
| 领域 | 心理测量学 | 心理测量学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 1971 | 1970s–1993 |
| 提出者≠ | Karl Jöreskog | William H. Angoff and colleagues (ETS); systematized by Holland & Wainer |
| 类型≠ | Measurement model / invariance test | Item-level bias detection |
| 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 ↗ | Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589 |
| 别名 | MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA | DIF, item bias analysis, measurement non-equivalence, item-level measurement bias |
| 相关≠ | 6 | 5 |
| 摘要≠ | 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. | Differential item functioning identifies test or survey items that behave differently for examinees from different groups — such as gender, ethnicity, or language background — after controlling for the underlying ability or trait being measured. DIF analysis is essential for fairness evaluation in educational testing and psychological scale development. |
| ScholarGate数据集 ↗ |
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