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| التحليل التفاضلي للأداء على البنود متعدد المستويات (DIF متعدد المستويات)× | Differential Item Functioning× | |
|---|---|---|
| المجال | القياس النفسي | القياس النفسي |
| العائلة | Latent structure | Latent structure |
| سنة النشأة≠ | 2001 | 1970s–1993 |
| صاحب الطريقة≠ | Kamata (2001) and subsequent multilevel IRT/DIF literature | William H. Angoff and colleagues (ETS); systematized by Holland & Wainer |
| النوع≠ | Bias detection / multilevel measurement model | Item-level bias detection |
| المصدر التأسيسي≠ | French, B. F., & Finch, W. H. (2008). Multigroup confirmatory factor analysis: Locating the invariant referent sets. Structural Equation Modeling: A Multidisciplinary Journal, 15(1), 96–113. DOI ↗ | Holland, P. W. & Wainer, H. (Eds.) (1993). Differential Item Functioning. Lawrence Erlbaum Associates. ISBN: 978-0805809589 |
| الأسماء البديلة | multilevel DIF, hierarchical DIF analysis, cross-level DIF, ML-DIF | DIF, item bias analysis, measurement non-equivalence, item-level measurement bias |
| ذات صلة | 5 | 5 |
| الملخص≠ | Multilevel DIF analysis detects whether individual test or survey items function differently across groups when respondents are clustered within higher-level units — such as students nested in schools, employees in organizations, or patients in clinics. By accounting for hierarchical data structure, it separates genuine item bias from artificial DIF signals caused by ignoring clustering. | 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. |
| ScholarGateمجموعة البيانات ↗ |
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