Sen Sedat, Cohen Allan S
Educational Sciences Department, Faculty of Education, Harran University, Sanliurfa, Turkey.
Educational Psychology Department, College of Education, University of Georgia, Athens, GA, United States.
Front Psychol. 2021 Jan 25;11:621251. doi: 10.3389/fpsyg.2020.621251. eCollection 2020.
Results of a comprehensive simulation study are reported investigating the effects of sample size, test length, number of attributes and base rate of mastery on item parameter recovery and classification accuracy of four DCMs (i.e., C-RUM, DINA, DINO, and LCDMREDUCED). Effects were evaluated using bias and RMSE computed between true (i.e., generating) parameters and estimated parameters. Effects of simulated factors on attribute assignment were also evaluated using the percentage of classification accuracy. More precise estimates of item parameters were obtained with larger sample size and longer test length. Recovery of item parameters decreased as the number of attributes increased from three to five but base rate of mastery had a varying effect on the item recovery. Item parameter and classification accuracy were higher for DINA and DINO models.
报告了一项全面模拟研究的结果，该研究调查了样本量、测试长度、属性数量和掌握基础率对四种诊断分类模型（即C-RUM、DINA、DINO和LCDMREDUCED）的项目参数恢复和分类准确性的影响。使用真实（即生成）参数和估计参数之间计算的偏差和均方根误差来评估影响。还使用分类准确率百分比评估了模拟因素对属性分配的影响。样本量越大、测试长度越长，项目参数的估计就越精确。随着属性数量从三个增加到五个，项目参数的恢复率下降，但掌握基础率对项目恢复有不同的影响。DINA和DINO模型的项目参数和分类准确率更高。
