A Rating Scale Mixture Model to Account for the Tendency to Middle and Extreme Categories

IF 1.9 3区 心理学 Q2 EDUCATION & EDUCATIONAL RESEARCH Journal of Educational and Behavioral Statistics Pub Date : 2021-03-31 DOI:10.3102/1076998621992554
R. Colombi, S. Giordano, G. Tutz
{"title":"A Rating Scale Mixture Model to Account for the Tendency to Middle and Extreme Categories","authors":"R. Colombi, S. Giordano, G. Tutz","doi":"10.3102/1076998621992554","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":48001,"journal":{"name":"Journal of Educational and Behavioral Statistics","volume":"46 1","pages":"682 - 716"},"PeriodicalIF":1.9000,"publicationDate":"2021-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Educational and Behavioral Statistics","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.3102/1076998621992554","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 2

Abstract

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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
考虑中等和极端类别倾向的评级量表混合模型
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。
求助全文
约1分钟内获得全文 去求助
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.
期刊最新文献
Improving Balance in Educational Measurement: A Legacy of E. F. Lindquist A Simple Technique Assessing Ordinal and Disordinal Interaction Effects A Comparison of Latent Semantic Analysis and Latent Dirichlet Allocation in Educational Measurement Sample Size Calculation and Optimal Design for Multivariate Regression-Based Norming Corrigendum to Power Approximations for Overall Average Effects in Meta-Analysis With Dependent Effect Sizes
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1