利克特尺度的差异项目功能分析:评级尺度树模型的概述和演示
Farshad Effatpanah1, Hamdollah Ravand2, Philipp Doebler3
1Research Unit of Psychological Assessment, Faculty of Rehabilitation Sciences, TU Dortmund University, Dortmund, Germany.
Psychological reports
|January 6, 2025
概括
评级规模树 (RStree) 模型有效地检测测试验焦虑量表中的差异项目功能 (DIF). 性别,而不是年龄,影响了项目表现,突出了RStree.
科学领域:
- 心理测量 心理测量 心理测量
- 教育心理学教育心理学
- 社会科学 社会科学 社会科学
背景情况:
- 差异性项目功能 (DIF) 对于心理测量评估至关重要,可以识别尺度中的偏差项目.
- 传统的DIF方法通常需要预先定义的子组,限制了检测细微群体差异的灵活性.
- 评级规模树 (RStree) 模型为DIF检测提供了一种新的方法,没有先验的组规范.
研究的目的:
- 为了证明RStree模型在社会科学研究中在利克特类型尺度中检测DIF的实用性.
- 在一个认知测试焦虑尺度中调查DIF,跨年龄和性别子组.
- 将RStree模型的性能与传统的DIF检测方法进行比较.
主要方法:
- 利用了721名英语外语 (EFL) 学生的项目响应数据.
- 应用RStree模型来分析认知测试焦虑量表上的反应.
- 检查了年龄和性别对物品响应模式的共变量的影响.
主要成果:
- 该RStree模型确定了三个不同的,非预定义的节点,表明项目难度的微妙变化.
- 认知测试焦虑量表上的四个项目被标记为差异性项目功能 (DIF).
- 发现性别是产生DIF的重要因素,而年龄没有显著影响.
结论:
- RStree模型有效地识别了在利克特类型尺度中的DIF,特别是在社会科学环境中.
- 性别,但不是年龄,在测试焦虑度的差异性项目功能中起作用.
- 该RStree模型成功地捕捉了受访者特征和规模项目之间的复杂相互作用.
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