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DIF Testing for Ordinal Items With Poly-SIBTEST, the Mantel and GMH Tests, and IRT-LR-DIF When the Latent Distribution Is Nonnormal for Both Groups

机译:当两组的潜在分布均非正态时,使用Poly-SIBTEST进行序号项目的DIF测试,Mantel和GMH测试以及IRT-LR-DIF

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摘要

Differential item functioning (DIF) occurs when an item on a test, questionnaire, or interview has different measurement properties for one group of people versus another. One way to test items with ordinal response scales for DIF is likelihood ratio (LR) testing using item response theory (IRT), or IRT-LR-DIF. Despite the various advantages of IRT-LR-DIF, one disadvantage is that the latent variable is usually assumed to be normally distributed. If this normality assumption is violated, nonparametric alternatives such as the Mantel test, generalized Mantel-Haenszel (GMH) test, and poly-SIBTEST may be preferable. Simulations were carried out to compare IRT-LR-DIF to poly-SIBTEST and the GMH and Mantel tests when the latent density is nonnormal for both groups but presumed normal for IRT-LR-DIF. Results indicated that latent nonnormality detrimentally affected all three procedures, but IRT-LR-DIF was surprisingly more robust to latent nonnormality than all of the nonparametric approaches.
机译:当测试,问卷调查或访谈中的一项对一组人与另一组人具有不同的度量属性时,就会发生差异项功能(DIF)。测试具有DIF顺序响应量表的项目的一种方法是使用项目响应理论(IRT)或IRT-LR-DIF进行似然比(LR)测试。尽管IRT-LR-DIF具有多种优点,但一个缺点是通常假定潜变量是正态分布的。如果违反了这种正态性假设,则最好使用非参数替代方案,例如Mantel检验,广义Mantel-Haenszel(GMH)检验和poly-SIBTEST。当两组的潜在密度均非正常但假定IRT-LR-DIF正常时,进行了模拟以将IRT-LR-DIF与poly-SIBTEST以及GMH和Mantel测试进行比较。结果表明,潜在的非正规性对所有三个过程均产生不利影响,但是IRT-LR-DIF令人惊讶地比所有非参数方法对潜在的非正规性更强大。

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