Freie Universität Berlin.
National Board of Medical Examiners.
Multivariate Behav Res. 2020 May-Jun;55(3):425-453. doi: 10.1080/00273171.2019.1643699. Epub 2019 Aug 26.
For adequate modeling of missing responses, a thorough understanding of the nonresponse mechanisms is vital. As a large number of major testing programs are in the process or already have been moving to computer-based assessment, a rich body of additional data on examinee behavior becomes easily accessible. These additional data may contain valuable information on the processes associated with nonresponse. Bringing together research on item omissions with approaches for modeling response time data, we propose a framework for simultaneously modeling response behavior and omission behavior utilizing timing information for both. As such, the proposed model allows (a) to gain a deeper understanding of response and nonresponse behavior in general and, in particular, of the processes underlying item omissions in LSAs, (b) to model the processes determining the time examinees require to generate a response or to omit an item, and (c) to account for nonignorable item omissions. Parameter recovery of the proposed model is studied within a simulation study. An illustration of the model by means of an application to real data is provided.
为了充分模拟缺失响应,深入了解非响应机制至关重要。随着大量主要测试计划正在或已经转向基于计算机的评估,大量关于考生行为的额外数据变得易于获取。这些额外的数据可能包含与非响应相关过程的有价值信息。将项目遗漏研究与响应时间数据建模方法相结合,我们提出了一个框架,用于同时利用时间信息对响应行为和遗漏行为进行建模。因此,所提出的模型允许:(a)更深入地了解一般的响应和非响应行为,特别是理解在 LSAs 中项目遗漏的背后过程;(b)对决定考生生成响应或遗漏项目所需时间的过程进行建模;(c)解释不可忽略的项目遗漏。在模拟研究中研究了拟议模型的参数恢复。通过对真实数据的应用来说明该模型。