Ma Wenchao, Terzi Ragip, de la Torre Jimmy
The University of Alabama, Tuscaloosa, USA.
Harran University, Sanliurfa, Turkey.
Appl Psychol Meas. 2021 Jan;45(1):37-53. doi: 10.1177/0146621620965745. Epub 2020 Oct 21.
This study proposes a multiple-group cognitive diagnosis model to account for the fact that students in different groups may use distinct attributes or use the same attributes but in different manners (e.g., conjunctive, disjunctive, and compensatory) to solve problems. Based on the proposed model, this study systematically investigates the performance of the likelihood ratio (LR) test and Wald test in detecting differential item functioning (DIF). A forward anchor item search procedure was also proposed to identify a set of anchor items with invariant item parameters across groups. Results showed that the LR and Wald tests with the forward anchor item search algorithm produced better calibrated Type I error rates than the ordinary LR and Wald tests, especially when items were of low quality. A set of real data were also analyzed to illustrate the use of these DIF detection procedures.
本研究提出了一种多组认知诊断模型，以解释不同组的学生可能使用不同的属性，或者使用相同的属性但以不同方式（例如，合取、析取和补偿）解决问题这一事实。基于所提出的模型，本研究系统地考察了似然比（LR）检验和 Wald 检验在检测项目功能差异（DIF）方面的性能。还提出了一种前向锚定项目搜索程序，以识别一组在不同组间具有不变项目参数的锚定项目。结果表明，与普通的 LR 和 Wald 检验相比，采用前向锚定项目搜索算法的 LR 和 Wald 检验产生了校准效果更好的 I 类错误率，尤其是当项目质量较低时。还分析了一组实际数据，以说明这些 DIF 检测程序的使用情况。
