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高维度问卷可以解决强制选择响应格式的Ipsativity问题吗?
Niklas Schulte1, Heinz Holling1, Paul-Christian Bürkner2
1University of Münster, Germany.
Educational and psychological measurement
|November 6, 2023
概括
强迫选择问卷,虽然减少了响应偏差,但通常会产生不可靠的分数. 模拟表明,即使有许多特征,古典和瑟斯顿的IRT方法在现实场景中都在与可靠性和可靠性作斗争.
科学领域:
- 心理测量 心理测量 心理测量
- 心理测量 心理测量
- 量化心理学 量化心理学
背景情况:
- 强制选择问卷减轻了评级尺度中常见的响应偏差.
- 然而,他们的分数往往是不可靠的和不确定的,阻碍了个人之间的比较.
- 提出了高维度来解决这些问题.
研究的目的:
- 调查在强制选择问卷中克服可靠性和ipsativity问题所需的特征数量.
- 在不同的条件下比较经典的评分和瑟斯顿的物品响应理论 (IRT) 模型.
主要方法:
- 进行了计算机模拟.
- 不同的参数包括样本大小,因子负载和间隙相关性.
- 研究了两种评分方法:古典 (ipsative) 和瑟斯顿的IRT.
主要成果:
- 在理想条件下,Thurstonian IRT 模型表现良好.
- 这两种方法在最现实的应用环境中都显示出不够的可靠性.
- 即使有30个特征,古典和瑟斯顿的IRT分数仍然是部分的.
结论:
- 高维度解决强制选择问卷中的ipsativity的假设受到质疑.
- 结果质疑使用Thurstonian IRT模型的ipsative分数的验证研究的解释性.
- 在强制选择问卷的实际应用中,可靠性和可比性问题仍然存在.
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