后验概率
贝叶斯概率
计算机科学
无效假设
集合(抽象数据类型)
统计假设检验
考试(生物学)
统计
考试成绩
人工智能
计量经济学
机器学习
数学
标准化测试
古生物学
生物
程序设计语言
作者
Sandip Sinharay,Matthew Johnson
标识
DOI:10.3102/1076998620957423
摘要
Score differencing is one of the six categories of statistical methods used to detect test fraud (Wollack & Schoenig, 2018) and involves the testing of the null hypothesis that the performance of an examinee is similar over two item sets versus the alternative hypothesis that the performance is better on one of the item sets. We suggest, to perform score differencing, the use of the posterior probability of better performance on one item set compared to another. In a simulation study, the suggested approach performs satisfactory compared to several existing approaches for score differencing. A real data example demonstrates how the suggested approach may be effective in detecting fraudulent examinees. The results in this article call for more attention to the use of posterior probabilities, and Bayesian approaches in general, in investigations of test fraud.
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