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模拟人猜测作为随机效应:贝叶斯对两个参数后勤模型的方法
Georgios Sideridis1, Mohammed Alghamdi2
1Boston Children's Hospital, Harvard Medical School, Boston, MA, United States.
Frontiers in psychology
|March 4, 2026
概括
这项研究引入了贝叶斯的随机效应模型,将猜测视为个体特征,提高了多选项的得分有效性. 新模型通过考虑各种猜测倾向来提高心理测量性能.
科学领域:
- 心理测量 心理测量 心理测量
- 教育测量教育的测量
- 统计建模 统计建模
背景情况:
- 在多项选择 (MC) 项目中猜测行为是一个持久的问题,影响得分的有效性和可解释性.
- 传统模型通常将猜测视为特定项目的参数,未能捕捉猜测倾向的个体差异.
研究的目的:
- 实现一个贝叶斯的随机效应扩展的两个参数后勤 (2PLE) 模型.
- 将猜测概念化和建模为潜在的个体特征,而不是固定的项目参数.
主要方法:
- 一个蒙特卡洛模拟研究进行了完全交叉设计.
- 在2PLE模型下模拟的项目响应数据,在各种样本大小 (N=100-1,000) 和测试长度 (6-40项) 中进行异质猜测.
- 贝叶斯预测性适合指数 (LOOIC,WAIC) 用于比较模型适合性.
主要成果:
- 拟议的2PLE随机效应模型与三参数后勤 (3PL) 模型相比显示出更高的性能.
- 用2PLE模型对项目歧视,难度和较低的对称值的估计更准确,特别是在异质猜测条件下.
- 贝叶斯适应指数在所有模拟条件中始终支持2PLE模型.
结论:
- 在2PLE随机效应框架内,从项目到个人重新分配猜测差异可以提高心理测量性能.
- 研究结果支持将猜测作为一个实质性的,基于特征的过程的概念化.
- 这项研究强调了针对个人的猜测模型的必要性,以优化测试成绩的推断.
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