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Item Response Theory Models for Wording Effects in Mixed-Format Scales

机译:混合格式量表中措辞效果的项目响应理论模型

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摘要

Many scales contain both positively and negatively worded items. Reverse recoding of negatively worded items might not be enough for them to function as positively worded items do. In this study, we commented on the drawbacks of existing approaches to wording effect in mixed-format scales and used bi-factor item response theory (IRT) models to test the assumption of reverse coding and evaluate the magnitude of the wording effect. The parameters of the bi-factor IRT models can be estimated with existing computer programs. Two empirical examples from the Program for International Student Assessment and the Trends in International Mathematics and Science Study were given to demonstrate the advantages of the bi-factor approach over traditional ones. It was found that the wording effect in these two data sets was substantial and that ignoring the wording effect resulted in overestimated test reliability and biased person measures.
机译:许多秤都包含正词和负词。负面词条的反向编码可能不足以使它们像正面词条那样起作用。在这项研究中,我们评论了混合格式量表中现有措辞效果方法的弊端,并使用了双因素项响应理论(IRT)模型来测试反向编码的假设并评估措辞效果的大小。双因素IRT模型的参数可以使用现有的计算机程序进行估算。给出了国际学生评估计划和国际数学与科学研究趋势的两个经验例子,以证明双因素方法相对于传统方法的优势。发现这两个数据集中的措词效果是巨大的,而忽略措辞效果会导致高估测试的可靠性和偏向人员的措施。

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