DIF 统计推断在不知情的情况下定项目
Yunxiao Chen1, Chengcheng Li2, Jing Ouyang2
1London School of Economics and Political Science, London, UK. y.chen186@lse.ac.uk.
Psychometrika
|August 7, 2023
概括
本研究引入了一种用于差异项目功能 (DIF) 分析的新方法,改进了测量不变性评估,而不需要预定义的点. 新方法为DIF检测提供了有效的统计推断,有效控制I型错误.
科学领域:
- 心理测量 心理测量 心理测量
- 统计建模 统计建模
- 测量的有效性测量有效性.
背景情况:
- 测量不变对于仪器有效性至关重要,通常使用差异物品功能 (DIF) 分析进行评估.
- 传统的DIF分析依赖于点项目,如果错误指定或未知,可能会有问题.
- 现有的方法,如项目净化和规范化,缺乏保证有效的统计推理.
研究的目的:
- 为多个指标和多个原因 (MIMIC) 模型提出新的DIF分析方法.
- 为了能够准确估计DIF效应和有效的统计推断,而没有先前的项目知识.
- 为了控制DIF检测中的I型错误率.
主要方法:
- 提出了一种新的DIF分析方法,在MIMIC模型中使用最小L0规范条件来识别潜在特征分布.
- 该方法估计了个别项目DIF效应,并量化了不确定性,而不依赖预先指定的点集.
- 通过模拟研究来评估性能,将其与基于集的概率比率测试和LASSO方法进行比较.
主要成果:
- 拟议的方法准确地估计了DIF效应,并提供了有效的统计推断,包括受控的I型错误率.
- 与现有方法相比,模拟研究证明了该方法的有效性.
- 该方法已成功应用于分析Eysenck人格调查问卷-修订 (EPQ-R) 中的人格尺度.
结论:
- 新的DIF分析方法提供了一个可靠的替代方案,当点不可用或错误指定时.
- 它提供了有效的统计推断,提高了测量不变性评估的可靠性.
- 这种方法有助于更准确和可靠的心理测量评估.
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