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A Comparative Analysis of the Efficacy of Differential Item Functioning Detection for Dichotomously Scored Items among Logistic Regression, SIBTEST and Raschtree Methods

机译:Logistic回归,SIBTEST和Raschtree方法对二分得分项目的差异项功能检测功效的比较分析

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A variety of statistical methods is available for detecting Differential Item Functioning (DIF) in the Rasch model. Most of these methods consist of two approaches. The first is based on the comparison of the item parametersestimate pre-specified groups of subjects. The second is based on a comparison between all possible groups of subjects, regardless of person covariates. The purpose of this research is to compare the efficiency of Differential Item Functioning (DIF) detection between three methods: (1) Logistic regression based on classical test theory; (2) SIBTEST based on item response theory and (3) Raschtree based on model-based recursive partitioning. Detection of DIF was collected through simulation. The first phase of the study revealed the advantages and disadvantages of these three methods from a literature review. The second phase of the research compared the efficiency of DIF detection using data simulation of four factors: type of item, number of DIF, test length and sample size.
机译:可以使用多种统计方法来检测Rasch模型中的差异项功能(DIF)。这些方法大多数由两种方法组成。第一种是基于项目参数的比较来估计预先指定的科目组。第二个是基于所有可能的受试者组之间的比较,而不考虑人的协变量。本研究的目的是比较三种方法之间的差异项功能(DIF)检测效率:(1)基于经典检验理论的Logistic回归; (2)基于项目响应理论的SIBTEST和(3)基于基于模型的递归分区的Raschtree。通过仿真收集DIF的检测。研究的第一阶段从文献综述中揭示了这三种方法的优缺点。研究的第二阶段使用四个因素的数据模拟比较了DIF检测的效率:四个因素:项目类型,DIF数量,测试长度和样本大小。

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