方法对比
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| 贝叶斯项目分析× | 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≠ | 1990s–2000s | 1970s–1993 |
| 提出者≠ | Originated in Bayesian psychometrics literature, developed extensively by Jean-Paul Fox and colleagues | William H. Angoff and colleagues (ETS); systematized by Holland & Wainer |
| 类型≠ | Bayesian inference / item-level diagnostics | Item-level bias detection |
| 开创性文献≠ | Fox, J.-P. (2010). Bayesian Item Response Modeling: Theory and Applications. Springer. DOI ↗ | Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589 |
| 别名 | BIA, Bayesian classical item analysis, Bayesian item statistics, Bayesian item-level diagnostics | DIF, item bias analysis, measurement non-equivalence, item-level measurement bias |
| 相关≠ | 4 | 5 |
| 摘要≠ | Bayesian item analysis applies Bayesian inference to estimate item-level statistics — difficulty, discrimination, and distractor effectiveness — by combining observed response data with prior knowledge. It produces full posterior distributions over item parameters rather than single point estimates, providing richer uncertainty information especially with small samples. | 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. |
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