反应混合模型:跨反应时间项目特征的异质性。

IF 2.9 2区 心理学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Psychometrika Pub Date : 2018-06-01 Epub Date: 2018-02-01 DOI:10.1007/s11336-017-9602-9
Dylan Molenaar, Paul de Boeck
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引用次数: 29

摘要

在反应和反应时间的项目反应理论建模中,通常假设不同反应时间的项目反应具有相同的特征。然而,如果受试者在解决测试项目时采用不同的反应过程,则可能会产生数据的异质性。这些差异可能是主题内效应,也就是说,一个主题可能在某些项目上使用特定的过程,而在其他项目上使用具有不同项目特征的不同过程。如果使用一个过程而不是另一个过程的概率取决于受试者的反应时间,则在受试者内部,跨反应时间的项目特征的异质性就会出现。本文提出了响应混合建模的方法来考虑这种异质性。与传统的混合建模对整个响应向量进行分类不同,响应混合建模涉及对响应向量中的单个元素进行分类。仿真研究表明,混合响应模型在参数恢复方面是可行的。此外,将反应混合模型应用于真实数据集,以说明其在调查跨反应时间的项目特征的主体内部异质性中的用途。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Response Mixture Modeling: Accounting for Heterogeneity in Item Characteristics across Response Times.

In item response theory modeling of responses and response times, it is commonly assumed that the item responses have the same characteristics across the response times. However, heterogeneity might arise in the data if subjects resort to different response processes when solving the test items. These differences may be within-subject effects, that is, a subject might use a certain process on some of the items and a different process with different item characteristics on the other items. If the probability of using one process over the other process depends on the subject's response time, within-subject heterogeneity of the item characteristics across the response times arises. In this paper, the method of response mixture modeling is presented to account for such heterogeneity. Contrary to traditional mixture modeling where the full response vectors are classified, response mixture modeling involves classification of the individual elements in the response vector. In a simulation study, the response mixture model is shown to be viable in terms of parameter recovery. In addition, the response mixture model is applied to a real dataset to illustrate its use in investigating within-subject heterogeneity in the item characteristics across response times.

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来源期刊
Psychometrika
Psychometrika 数学-数学跨学科应用
CiteScore
4.40
自引率
10.00%
发文量
72
审稿时长
>12 weeks
期刊介绍: The journal Psychometrika is devoted to the advancement of theory and methodology for behavioral data in psychology, education and the social and behavioral sciences generally. Its coverage is offered in two sections: Theory and Methods (T& M), and Application Reviews and Case Studies (ARCS). T&M articles present original research and reviews on the development of quantitative models, statistical methods, and mathematical techniques for evaluating data from psychology, the social and behavioral sciences and related fields. Application Reviews can be integrative, drawing together disparate methodologies for applications, or comparative and evaluative, discussing advantages and disadvantages of one or more methodologies in applications. Case Studies highlight methodology that deepens understanding of substantive phenomena through more informative data analysis, or more elegant data description.
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