方法对比
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| 稳健项目分析× | 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≠ | 1980s–2000s | 1970s–1993 |
| 提出者≠ | Robust methods tradition (Huber, Hampel, Tukey); applied to item analysis by Wilcox and colleagues | William H. Angoff and colleagues (ETS); systematized by Holland & Wainer |
| 类型≠ | Diagnostic / item-level evaluation | Item-level bias detection |
| 开创性文献≠ | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838 | Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589 |
| 别名≠ | robust item statistics, outlier-resistant item analysis, robust classical item analysis | DIF, item bias analysis, measurement non-equivalence, item-level measurement bias |
| 相关 | 5 | 5 |
| 摘要≠ | Robust item analysis applies outlier-resistant statistical methods to the evaluation of individual test or scale items. Instead of classical means and Pearson correlations — both sensitive to extreme scores — it uses trimmed means, Winsorized correlations, or M-estimators to obtain item difficulty and item-total discrimination indices that remain stable when respondent distributions are skewed or contaminated by outliers. | 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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