Humphrey Stephen N
Stephen Mark Humphry, Graduate School of Education, University of Western Australia, M428, 35 Stirling Hwy., Crawley, WA 6009, Australia,
J Appl Meas. 2018;19(3):216-228.
Aligning scales in vertical equating carries a number of challenges for practitioners in contexts such as large-scale testing. This paper examines the impact of high and low discrimination on the results of vertical equating when the Rasch model is applied. A simulation study is used to show that different levels of discrimination introduce systematic error into estimates. A second simulation study shows that for the purpose of vertical equating, items with high or low discrimination contain information about translation constants that contains systematic error. The impact of differential item discrimination on vertical equating is examined and subsequently illustrated in terms of a real data set from a large-scale testing program, with vertical links between grade 3 and 5 numeracy tests. Implications of the results for practitioners conducting vertical equating with the Rasch model are identified, including monitoring progress over time. Implications for other item response models are also discussed.
在诸如大规模测试等情境中，垂直等值中的量表对齐给从业者带来了诸多挑战。本文研究了应用拉施模型时，高低区分度对垂直等值结果的影响。一项模拟研究表明，不同水平的区分度会给估计值引入系统误差。另一项模拟研究表明，就垂直等值而言，区分度高或低的项目所包含的关于平移常数的信息存在系统误差。研究了项目区分度差异对垂直等值的影响，并随后以一个大规模测试项目的真实数据集为例进行说明，该数据集中三年级和五年级的数学测试之间存在垂直关联。确定了这些结果对使用拉施模型进行垂直等值的从业者的影响，包括随时间监测进展情况。还讨论了对其他项目反应模型的影响。
