方法对比
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| 计算机化自适应测验项目功能差异 (CAT-DIF)× | 多组别项目功能差异 (MG-DIF)× | |
|---|---|---|
| 领域 | 心理测量学 | 心理测量学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 1990s–2000s | 1980s-1990s |
| 提出者≠ | Wainer, Zwick, and colleagues in the CAT and DIF literatures | Shealy & Stout (SIBTEST framework); Lord (IRT-based DIF) |
| 类型≠ | Item bias detection in adaptive testing | Measurement bias detection |
| 开创性文献≠ | Zwick, R., Thayer, D. T., & Mazzeo, J. (1997). Describing and categorizing DIF in polytomous items. Journal of Educational Measurement, 34(4), 261–285. DOI ↗ | Millsap, R. E. (2012). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 |
| 别名 | CAT DIF analysis, adaptive test DIF, DIF in computerized adaptive testing, CAT item bias detection | MG-DIF, multi-group DIF, differential item functioning across groups, multiple-group DIF analysis |
| 相关 | 6 | 6 |
| 摘要≠ | CAT-DIF identifies items in a computerized adaptive test that behave differently across demographic or group subpopulations after controlling for overall ability. Because adaptive algorithms select items non-randomly based on each examinee's estimated proficiency, standard DIF detection methods require adjustment before they can be validly applied in this context. | Multi-group differential item functioning examines whether test or scale items function equivalently across three or more distinct groups — such as gender, ethnicity, or country — after matching respondents on the underlying trait being measured. Items that behave differently across groups threaten fair measurement and valid score comparisons. |
| ScholarGate数据集 ↗ |
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