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On Wald tests for differential item functioning detection

机译:在Wald检验中进行差异项功能检测

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Wald-type tests are a common procedure for DIF detection among the IRT-based methods. However, the empirical type I error rate of these tests departs from the significance level. In this paper, two reasons that explain this discrepancy will be discussed and a new procedure will be proposed. The first reason is related to the equating coefficients used to convert the item parameters to a common scale, as they are treated as known constants whereas they are estimated. The second reason is related to the parameterization used to estimate the item parameters, which is different from the usual IRT parameterization. Since the item parameters in the usual IRT parameterization are obtained in a second step, the corresponding covariance matrix is approximated using the delta method. The proposal of this article is to account for the estimation of the equating coefficients treating them as random variables and to use the untransformed (i.e. not reparameterized) item parameters in the computation of the test statistic. A simulation study is presented to compare the performance of this new proposal with the currently used procedure. Results show that the new proposal gives type I error rates closer to the significance level.
机译:在基于IRT的方法中,Wald型测试是DIF检测的常见过程。但是,这些测试的经验I类错误率偏离了显着性水平。在本文中,将讨论解释这种差异的两个原因,并提出新的程序。第一个原因与用于将项目参数转换为通用标度的等价系数有关,因为它们被视为已知常数,而被估计。第二个原因与用于估算项目参数的参数化有关,这不同于通常的IRT参数化。由于在第二步中获得了常规IRT参数化中的项目参数,因此使用delta方法对相应的协方差矩阵进行了近似。本文的建议是考虑将等式系数视为随机变量的估计系数,并在测试统计量的计算中使用未转换(即未重新参数化)的项目参数。进行了仿真研究,以比较此新建议与当前使用的程序的性能。结果表明,新提议使I类错误率更接近显着性水平。

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