Computer-based testing (CBT) is becoming increasingly popular in assessing test-takers’ latent abilities and making inferences regarding their cognitive processes. In addition to collecting item responses, an important benefit of using CBT is that response times (RTs) can also be recorded and used in subsequent analyses. To better understand the structural relations between multidimensional cognitive attributes and the working speed of test-takers, this research proposes a joint-modeling approach that integrates compensatory multidimensional latent traits and response speediness using item responses and RTs. The joint model is cast as a multilevel model in which the structural relation between working speed and accuracy are connected through their variance-covariance structures. The feasibility of this modeling approach is investigated via a Monte Carlo simulation study using a Bayesian estimation scheme. The results indicate that integrating RTs increased model parameter recovery and precision. In addition, Program of International Student Assessment (PISA) 2015 mathematics standard unit items are analyzed to further evaluate the feasibility of the approach to recover model parameters.

中文翻译：

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补偿性多维项目响应和响应时间的联合建模。

基于计算机的测试 (CBT) 在评估考生的潜在能力并对其认知过程进行推断方面变得越来越流行。除了收集项目响应之外，使用 CBT 的一个重要好处是还可以记录响应时间 (RT) 并在后续分析中使用。为了更好地理解多维认知属性与考生工作速度之间的结构关系，本研究提出了一种联合建模方法，该方法利用项目响应和反应时间整合补偿性多维潜在特征和响应速度。联合模型被构建为多级模型，其中工作速度和精度之间的结构关系通过它们的方差-协方差结构连接起来。通过使用贝叶斯估计方案的蒙特卡罗模拟研究研究了这种建模方法的可行性。结果表明，整合 RT 提高了模型参数恢复率和精度。此外，还对国际学生评估计划（PISA）2015年数学标准单元项目进行了分析，进一步评估了模型参数恢复方法的可行性。