Song Lihong, Wang Wenyi
School of Education, Jiangxi Normal University, Nanchang, China.
School of Computer and Information Engineering, Jiangxi Normal University, Nanchang, China.
Appl Psychol Meas. 2025 Jan 28:01466216251316276. doi: 10.1177/01466216251316276.
Under the theory of sequential design, compound optimal design with two optimality criteria can be used to solve the problem of efficient calibration of item parameters of item response theory model. In order to efficiently calibrate item parameters in computerized testing, a compound optimal design is proposed for the simultaneous estimation of item difficulty and discrimination parameters under the two-parameter logistic model, which adaptively focuses on optimizing the parameter which is difficult to estimate. The compound optimal design using the acceptance probability can provide ability design points to optimize the item difficulty and discrimination parameters, respectively. Simulation and real data analysis studies showed that the compound optimal design outperformed than the D-optimal and random design in terms of the recovery of both discrimination and difficulty parameters.
在序贯设计理论下，具有两个最优性准则的复合最优设计可用于解决项目反应理论模型中项目参数的有效校准问题。为了在计算机化测试中有效校准项目参数，针对双参数逻辑模型下项目难度和区分度参数的同时估计提出了一种复合最优设计，该设计自适应地专注于优化难以估计的参数。使用接受概率的复合最优设计可以提供能力设计点，分别用于优化项目难度和区分度参数。模拟和实际数据分析研究表明，在区分度和难度参数的恢复方面，复合最优设计优于D最优设计和随机设计。
