Mulder Joris, van der Linden Wim J
Department of Research Methodology, Measurement, and Data Analysis, Twente University, P.O. Box 217, 7500 AE Enschede, The Netherlands.
Psychometrika. 2009 Jun;74(2):273-296. doi: 10.1007/s11336-008-9097-5. Epub 2008 Dec 23.
Several criteria from the optimal design literature are examined for use with item selection in multidimensional adaptive testing. In particular, it is examined what criteria are appropriate for adaptive testing in which all abilities are intentional, some should be considered as a nuisance, or the interest is in the testing of a composite of the abilities. Both the theoretical analyses and the studies of simulated data in this paper suggest that the criteria of A-optimality and D-optimality lead to the most accurate estimates when all abilities are intentional, with the former slightly outperforming the latter. The criterion of E-optimality showed occasional erratic behavior for this case of adaptive testing, and its use is not recommended. If some of the abilities are nuisances, application of the criterion of A(s)-optimality (or D(s)-optimality), which focuses on the subset of intentional abilities is recommended. For the measurement of a linear combination of abilities, the criterion of c-optimality yielded the best results. The preferences of each of these criteria for items with specific patterns of parameter values was also assessed. It was found that the criteria differed mainly in their preferences of items with different patterns of values for their discrimination parameters.
本文研究了最优设计文献中的几个准则在多维自适应测试中用于项目选择的情况。具体而言,研究了哪些准则适用于所有能力都是目标能力、有些能力应被视为干扰因素或者关注能力组合测试的自适应测试。本文的理论分析和模拟数据研究均表明,当所有能力都是目标能力时,A最优性准则和D最优性准则能得出最准确的估计,前者略优于后者。对于这种自适应测试情况,E最优性准则偶尔会出现不稳定行为,不建议使用。如果某些能力是干扰因素,建议应用专注于目标能力子集的A(s)最优性准则(或D(s)最优性准则)。对于能力线性组合的测量,c最优性准则产生了最佳结果。还评估了这些准则对具有特定参数值模式项目的偏好。结果发现,这些准则的主要差异在于对具有不同区分参数值模式项目的偏好。