Bayesian Logistic Regression: A New Method to Calibrate Pretest Items in Multistage Adaptive Testing

IF 1.1 4区 教育学 Q3 EDUCATION & EDUCATIONAL RESEARCH
TsungHan Ho
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引用次数: 0

Abstract

ABSTRACTAn operational multistage adaptive test (MST) requires the development of a large item bank and the effort to continuously replenish the item bank due to concerns about test security and validity over the long term. New items should be pretested and linked to the item bank before being used operationally. The linking item volume fluctuations in MST, however, bring into question the quality of the link to the reference scale. In this study, various calibration/linking methods along with a newly proposed Bayesian logistic regression (BLR) method were evaluated by comparison with the test characteristic curve method through simulated MST response data in terms of item parameter recovery. Results generated by the BLR method were promising due to its estimation stability and robustness across studied conditions. The findings of the present study should help inform practitioners of the utilities of implementing the pretest item calibration method in MST. Disclosure statementNo potential conflict of interest was reported by the author(s).
贝叶斯逻辑回归:一种校正多阶段自适应测试中预测项目的新方法
摘要一个可操作的多阶段自适应测试(MST)需要开发一个大型的题库,并且由于对测试安全性和长期有效性的考虑,需要不断地补充题库。在实际使用之前,新项目应预先测试并链接到题库。然而,MST中链接项目数量的波动使人们对与参考量表的链接质量产生了疑问。在本研究中,通过模拟MST响应数据,对各种校准/链接方法以及新提出的贝叶斯逻辑回归(BLR)方法与试验特征曲线方法在项目参数恢复方面进行了比较。由于BLR方法在研究条件下的估计稳定性和鲁棒性,其结果是有希望的。本研究的结果应有助于告知实践者在MST中实施测前项目校准方法的效用。披露声明作者未报告潜在的利益冲突。
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来源期刊
CiteScore
2.50
自引率
13.30%
发文量
14
期刊介绍: Because interaction between the domains of research and application is critical to the evaluation and improvement of new educational measurement practices, Applied Measurement in Education" prime objective is to improve communication between academicians and practitioners. To help bridge the gap between theory and practice, articles in this journal describe original research studies, innovative strategies for solving educational measurement problems, and integrative reviews of current approaches to contemporary measurement issues. Peer Review Policy: All review papers in this journal have undergone editorial screening and peer review.
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