Wang Wen-Chung, Chen Hui-Fang, Jin Kuan-Yu
The Hong Kong Institute of Education, Hong Kong SAR.
City University of Hong Kong, Hong Kong SAR.
Educ Psychol Meas. 2015 Feb;75(1):157-178. doi: 10.1177/0013164414528209. Epub 2014 Apr 6.
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.
许多量表同时包含正向表述和负向表述的项目。对负向表述的项目进行反向编码,可能不足以使其发挥正向表述项目的作用。在本研究中,我们评论了混合格式量表中现有措辞效应方法的缺点,并使用双因素项目反应理论(IRT)模型来检验反向编码的假设,并评估措辞效应的大小。双因素IRT模型的参数可以用现有的计算机程序进行估计。给出了国际学生评估项目和国际数学与科学研究趋势中的两个实证例子,以证明双因素方法相对于传统方法的优势。研究发现,这两个数据集中的措辞效应相当大,而忽略措辞效应会导致测试信度被高估和个体测量有偏差。