考虑中等和极端类别倾向的评级量表混合模型

IF 1.9 3区 心理学 Q2 EDUCATION & EDUCATIONAL RESEARCH
R. Colombi, S. Giordano, G. Tutz
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引用次数: 2

摘要

我们提出了一种混合的logit模型,用于区分对评分问题的回答,这些问题受不考虑项目内容(回答风格)而倾向于选择量表的中间或极端的倾向的影响,以及纯粹的内容驱动的偏好。解释变量用于描述内容驱动的回答方式,以及趋向于中间或极端类别。所建议的模型被扩展为在多个项目的情况下考虑响应风格的存在,并且描述了响应之间的关联,无论是内容驱动的还是由响应风格决定的。此外,引入并研究了与选择中间或极端类别的倾向有关的随机排序。仿真研究表明了该模型的有效性,并通过对少数民族态度问卷调查的应用说明了该模型方法的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Rating Scale Mixture Model to Account for the Tendency to Middle and Extreme Categories
A mixture of logit models is proposed that discriminates between responses to rating questions that are affected by a tendency to prefer middle or extremes of the scale regardless of the content of the item (response styles) and purely content-driven preferences. Explanatory variables are used to characterize the content-driven way of answering as well as the tendency to middle or extreme categories. The proposed model is extended to account for the presence of response styles in the case of several items, and the association among responses is described, both when they are content driven or dictated by response styles. In addition, stochastic orderings, related to the tendency to select middle or extreme categories, are introduced and investigated. A simulation study describes the effectiveness of the proposed model, and an application to a questionnaire on attitudes toward ethnic minorities illustrates the applicability of the modeling approach.
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来源期刊
CiteScore
4.40
自引率
4.20%
发文量
21
期刊介绍: Journal of Educational and Behavioral Statistics, sponsored jointly by the American Educational Research Association and the American Statistical Association, publishes articles that are original and provide methods that are useful to those studying problems and issues in educational or behavioral research. Typical papers introduce new methods of analysis. Critical reviews of current practice, tutorial presentations of less well known methods, and novel applications of already-known methods are also of interest. Papers discussing statistical techniques without specific educational or behavioral interest or focusing on substantive results without developing new statistical methods or models or making novel use of existing methods have lower priority. Simulation studies, either to demonstrate properties of an existing method or to compare several existing methods (without providing a new method), also have low priority. The Journal of Educational and Behavioral Statistics provides an outlet for papers that are original and provide methods that are useful to those studying problems and issues in educational or behavioral research. Typical papers introduce new methods of analysis, provide properties of these methods, and an example of use in education or behavioral research. Critical reviews of current practice, tutorial presentations of less well known methods, and novel applications of already-known methods are also sometimes accepted. Papers discussing statistical techniques without specific educational or behavioral interest or focusing on substantive results without developing new statistical methods or models or making novel use of existing methods have lower priority. Simulation studies, either to demonstrate properties of an existing method or to compare several existing methods (without providing a new method), also have low priority.
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