On a Reparameterization of the MC-DINA Model.

IF 1 4区 心理学 Q4 PSYCHOLOGY, MATHEMATICAL
Lawrence T DeCarlo
{"title":"On a Reparameterization of the MC-DINA Model.","authors":"Lawrence T DeCarlo","doi":"10.1177/01466216251324938","DOIUrl":null,"url":null,"abstract":"<p><p>The MC-DINA model is a cognitive diagnosis model (CDM) for multiple-choice items that was introduced by de la Torre (2009). The model extends the usual CDM in two basic ways: it allows for nominal responses instead of only dichotomous responses, and it allows skills to affect not only the choice of the correct response but also the choice of distractors. Here it is shown that the model can be re-expressed as a multinomial logit model with latent discrete predictors, that is, as a multinomial mixture model; a signal detection-like parameterization is also used. The reparameterization clarifies details about the structure and assumptions of the model, especially with respect to distractors, and helps to reveal parameter restrictions, which in turn have implications for psychological interpretations of the data and for issues with respect to statistical estimation. The approach suggests parsimonious models that are useful for practical applications, particularly for small sample sizes. The restrictions are shown to appear for items from the TIMSS 2007 fourth grade exam.</p>","PeriodicalId":48300,"journal":{"name":"Applied Psychological Measurement","volume":" ","pages":"01466216251324938"},"PeriodicalIF":1.0000,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11897991/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Psychological Measurement","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1177/01466216251324938","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PSYCHOLOGY, MATHEMATICAL","Score":null,"Total":0}
引用次数: 0

Abstract

The MC-DINA model is a cognitive diagnosis model (CDM) for multiple-choice items that was introduced by de la Torre (2009). The model extends the usual CDM in two basic ways: it allows for nominal responses instead of only dichotomous responses, and it allows skills to affect not only the choice of the correct response but also the choice of distractors. Here it is shown that the model can be re-expressed as a multinomial logit model with latent discrete predictors, that is, as a multinomial mixture model; a signal detection-like parameterization is also used. The reparameterization clarifies details about the structure and assumptions of the model, especially with respect to distractors, and helps to reveal parameter restrictions, which in turn have implications for psychological interpretations of the data and for issues with respect to statistical estimation. The approach suggests parsimonious models that are useful for practical applications, particularly for small sample sizes. The restrictions are shown to appear for items from the TIMSS 2007 fourth grade exam.

MC-DINA模型的一种再参数化。
MC-DINA模型是de la Torre(2009)提出的多选题认知诊断模型(CDM)。该模型以两种基本方式扩展了通常的CDM:它允许名义反应,而不仅仅是二分反应;它允许技能不仅影响正确反应的选择,还影响干扰因素的选择。结果表明,该模型可以重新表示为具有潜在离散预测因子的多项logit模型,即多项混合模型;还使用了类似信号检测的参数化。重新参数化澄清了关于模型结构和假设的细节,特别是关于干扰因素,并有助于揭示参数限制,这反过来又对数据的心理解释和统计估计方面的问题产生影响。这种方法提出了对实际应用有用的精简模型,特别是对小样本量。这些限制出现在TIMSS 2007年四年级考试的项目中。
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 求助全文
来源期刊
CiteScore
2.30
自引率
8.30%
发文量
50
期刊介绍: Applied Psychological Measurement publishes empirical research on the application of techniques of psychological measurement to substantive problems in all areas of psychology and related disciplines.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信