Using Ordering Theory to Learn Attribute Hierarchies From Examinees’ Attribute Profiles

Yuzhi Yan, Shenghong Dong and Xiaofeng Yu

Journal of Educational and Behavioral Statistics, 2025, vol. 50, issue 6, 985-1013

Abstract: In cognitive diagnosis, attribute hierarchies are considered important structural features of cognitive diagnostic models, as they provide auxiliary information about the nature of attributes. In this article, the idea of ordering theory is applied to cognitive diagnosis, and a new approach to identify attribute hierarchy based on the attribute correlation intensity matrix is proposed. This approach attempts to identify attribute hierarchy in data with a small sample size while ensuring a high accuracy rate. The results of simulation studies and empirical data analysis show that the proposed approach can be used to identify attribute hierarchy in diagnostic tests, especially in small samples, making it worth popularizing.

Keywords: cognitive diagnostic; attribute hierarchy; ordering theory; attribute correlation intensity matrix (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.3102/10769986241280389 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:50:y:2025:i:6:p:985-1013

DOI: 10.3102/10769986241280389

Access Statistics for this article

More articles in Journal of Educational and Behavioral Statistics
Bibliographic data for series maintained by SAGE Publications ().