一般属性结构上合取模型中的完全q矩阵

IF 1.5 3区 心理学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS British Journal of Mathematical & Statistical Psychology Pub Date : 2022-03-20 DOI:10.1111/bmsp.12266
Jürgen Heller
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引用次数: 0

摘要

在认知诊断评估中,q矩阵的一个属性,通常被称为完整性,保证了观察到的行为背后的认知属性可以被唯一地评估。完备性的特征首先是在独立属性的假设下推导出来的,目前正在对相互依赖属性进行研究。占主导地位的方法考虑所谓的属性层次结构,它通过属性集上的偏序来概念化。本文扩展了先前发表的关于连接属性层次模型的结果。利用知识结构理论的结果,它不仅为属性层次上的合取模型,而且为更一般的属性结构上的合取模型提供了新的q矩阵完备性的充要条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Complete Q-matrices in conjunctive models on general attribute structures

In cognitive diagnostic assessment a property of the Q-matrix, usually referred to as completeness, warrants that the cognitive attributes underlying the observed behaviour can be uniquely assessed. Characterizations of completeness were first derived under the assumption of independent attributes, and are currently under investigation for interdependent attributes. The dominant approach considers so-called attribute hierarchies, which are conceptualized through a partial order on the set of attributes. The present paper extends previously published results on this issue obtained for conjunctive attribute hierarchy models. Drawing upon results from knowledge structure theory, it provides novel sufficient and necessary conditions for completeness of the Q-matrix, not only for conjunctive models on attribute hierarchies, but also on more general attribute structures.

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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.
期刊最新文献
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