贝叶斯适应拉索用于检测多维物件响应理论模型中的项目-特征关系和差异性项目功能
Na Shan1, Ping-Feng Xu2,3
1School of Psychology & Key Laboratory of Applied Statistics of MOE, Northeast Normal University, 5268 Renmin Street, Changchun, Jilin, China. shanna1981@126.com.
Psychometrika
|August 10, 2024
概括
本研究引入了一个统一的框架,用于同时检测物品-特征关系和差异物品功能 (DIF) 在多维物品响应理论 (MIRT) 模型中,使用贝叶斯适应拉索程序.
科学领域:
- 心理测量 心理测量 心理测量
- 统计建模 统计建模
- 教育测量的教育测量.
背景情况:
- 在多维测试中,精确识别潜在特征是必不可少的.
- 差异性项目功能 (DIF) 对于有效的组比较至关重要,但通常与项目-特征关系分开研究.
研究的目的:
- 在多维项目响应理论 (MIRT) 模型中开发一个统一的框架来检测项目-特征关系和DIF.
- 将DIF效应集成到MIRT模型中,作为潜在/观察变量及其相互作用的变量选择问题.
主要方法:
- 一个贝叶斯适应拉索程序被开发用于同时选择变量.
- 这种方法可以同时估计项目-特征关系和DIF效应.
主要成果:
- 模拟研究证明了该方法在参数估计中的有效性.
- 该程序成功地恢复了项目-特征关系,并检测了DIF效应.
结论:
- 拟议的统一框架和贝叶斯适应拉索程序为分析多维项目响应数据提供了强大的方法.
- 这种方法提高了潜在特征识别的准确性,并通过同时解决项目-特征关系和DIF,确保了不同组之间的公平性.
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