测试差异物品功能检测与多种物品在多层次数据中的测试
Sijia Huang1, Dubravka Svetina Valdivia1
1Indiana University Bloomington, USA.
Educational and psychological measurement
|May 17, 2024
概括
本研究引入了一种新的方法,用于检测多层次评估中的差异性项目功能 (DIF) 与多种类型的项目. 该方法有效地识别了有偏见的项目,确保了所有参与者的更公平的测试.
科学领域:
- 教育测量教育的测量
- 心理测量 心理测量 心理测量
- 统计 统计 统计 统计
背景情况:
- 评估中的公平衡量需要识别差异性项目功能 (DIF).
- 在多层数据结构中检测DIF是一个重大挑战,现有方法无法完全解决这个问题.
- 在许多评估中常见的多种项目增加了DIF分析的复杂性.
研究的目的:
- 引入一种新的程序,用于在多层数据中检测多种类型的项目中的统一和非统一的DIF.
- 扩展现有的两阶段DIF检测程序,以适应多层数据结构.
主要方法:
- 一个基于Lord's Wald chi-squared测试的程序被开发用于DIF检测.
- 大都会 - 黑斯廷斯 - 罗宾斯 - 蒙罗 (MH-RM) 算法用于估计多层多种物体响应理论 (IRT) 模型和协差矩阵.
- 采用了两阶段的方法,包括确定点,然后对候选项进行评估.
主要成果:
- 提出的方法在识别DIF项目方面表现出了很高的力量.
- 该方法有效控制了模拟研究中的I型错误率.
- 在模拟真实世界数据的各种模拟条件下,该程序是稳健的.
结论:
- 开发的程序提供了一种强大而可靠的方法,用于在多层次评估数据中检测多种物品中的DIF.
- 这一进步有助于通过提供工具来识别和解决复杂数据结构中的项目偏差来实现更公平的测量.
- 进一步的研究应该探索这个多层次的DIF检测方法的额外条件和应用.
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