Determining the number of attributes in the GDINA model.

IF 1.5 3区 心理学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS British Journal of Mathematical & Statistical Psychology Pub Date : 2024-06-18 DOI:10.1111/bmsp.12349
Juntao Wang, Jiangtao Duan
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Abstract

Exploratory cognitive diagnosis models have been widely used in psychology, education and other fields. This paper focuses on determining the number of attributes in a widely used cognitive diagnosis model, the GDINA model. Under some conditions of cognitive diagnosis models, we prove that there exists a special structure for the covariance matrix of observed data. Due to the special structure of the covariance matrix, an estimator based on eigen-decomposition is proposed for the number of attributes for the GDINA model. The performance of the proposed estimator is verified by simulation studies. Finally, the proposed estimator is applied to two real data sets Examination for the Certificate of Proficiency in English (ECPE) and Big Five Personality (BFP).

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确定 GDINA 模型的属性数量。
探索性认知诊断模型已广泛应用于心理学、教育学和其他领域。本文主要研究如何确定一种广泛使用的认知诊断模型--GDINA 模型--中的属性数量。在认知诊断模型的某些条件下,我们证明了观察数据的协方差矩阵存在一种特殊结构。基于协方差矩阵的特殊结构,我们提出了一种基于特征分解的 GDINA 模型属性数估计器。模拟研究验证了所提估计器的性能。最后,将所提出的估计器应用于两个真实数据集:英语水平证书考试(ECPE)和大五人格(BFP)。
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来源期刊
CiteScore
5.00
自引率
3.80%
发文量
34
审稿时长
>12 weeks
期刊介绍: The British Journal of Mathematical and Statistical Psychology publishes articles relating to areas of psychology which have a greater mathematical or statistical aspect of their argument than is usually acceptable to other journals including: • mathematical psychology • statistics • psychometrics • decision making • psychophysics • classification • relevant areas of mathematics, computing and computer software These include articles that address substantitive psychological issues or that develop and extend techniques useful to psychologists. New models for psychological processes, new approaches to existing data, critiques of existing models and improved algorithms for estimating the parameters of a model are examples of articles which may be favoured.
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