Assessing and Explaining Differential Item Functioning Using Logistic Mixed Models
Assessing and Explaining Differential Item Functioning Using Logistic Mixed Models
复制标题
使用逻辑混合模型评估和解释差异项目功能
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
P. De Boeck
中科院分区：
文献类型：
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作者：
W. Van den Noortgate;P. De Boeck
虽然差异项目功能（DIF）理论传统上侧重于两个（或几个）特定群体中单个项目的行为，但在教育测量背景下，将项目集视为更广泛类别中的随机样本通常是合理的。本文提出了logistic混合模型，可以用来模拟均匀的DIF，处理项目的影响和他们的相互作用与组（DIF）的随机。以类似的方式，如果组可以被认为是来自组的总体的随机样本，则组效应可以被建模为随机而不是固定。此外，该模型可以容易地适用于对个体而不是群体的DIF进行建模，或者用于对项目组而不是个体项目的差异功能进行建模。结果表明，logistic混合模型方法不仅是一种全面和经济的方式来检测这些不同类型的DIF，它也鼓励我们探索可能的解释DIF包括组或项目的协变量在模型中。
Although differential item functioning (DIF) theory traditionally focuses on the behavior of individual items in two (or a few) specific groups, in educational measurement contexts, it is often plausible to regard the set of items as a random sample from a broader category. This article presents logistic mixed models that can be used to model uniform DIF, treating the item effects and their interaction with groups (DIF) as random. In a similar way, the group effects can be modeled as random instead of fixed, if the groups can be considered a random sample from a population of groups. The models can, furthermore, be adapted easily for modeling DIF over individual persons rather than over groups, or for modeling the differential functioning of groups of items instead of individual items. It is shown that the logistic mixed model approach is not only a comprehensive and economical way to detect these different kinds of DIF, it also encourages us to explore possible explanations of DIF by including group or item covariates in the model.