DINA Model and Parameter Estimation: A Didactic
Jimmy de la Torre
Journal of Educational and Behavioral Statistics, 2009, vol. 34, issue 1, 115-130
Abstract:
Cognitive and skills diagnosis models are psychometric models that have immense potential to provide rich information relevant for instruction and learning. However, wider applications of these models have been hampered by their novelty and the lack of commercially available software that can be used to analyze data from this psychometric framework. To address this issue, this article focuses on one tractable and interpretable skills diagnosis model—the DINA model—and presents it didactically. The article also discusses expectation-maximization and Markov chain Monte Carlo algorithms in estimating its model parameters. Finally, analyses of simulated and real data are presented.
Keywords: cognitive diagnosis; skills diagnosis; DINA; Markov chain Monte Carlo; expectation-maximization; parameter estimation (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
https://journals.sagepub.com/doi/10.3102/1076998607309474 (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:34:y:2009:i:1:p:115-130
DOI: 10.3102/1076998607309474
Access Statistics for this article
More articles in Journal of Educational and Behavioral Statistics
Bibliographic data for series maintained by SAGE Publications ().