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DINA Model and Parameter Estimation: A Didactic

Author

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  • Jimmy de la Torre

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.

Suggested Citation

  • Jimmy de la Torre, 2009. "DINA Model and Parameter Estimation: A Didactic," Journal of Educational and Behavioral Statistics, , vol. 34(1), pages 115-130, March.
    • Handle: RePEc:sae:jedbes:v:34:y:2009:i:1:p:115-130
    DOI: 10.3102/1076998607309474
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    Citations

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    Cited by:

    1. Alexander Weissman, 2013. "Optimizing information using the EM algorithm in item response theory," Annals of Operations Research, Springer, vol. 206(1), pages 627-646, July.
    2. Hans-Friedrich Köhn & Chia-Yi Chiu, 2018. "How to Build a Complete Q-Matrix for a Cognitively Diagnostic Test," Journal of Classification, Springer;The Classification Society, vol. 35(2), pages 273-299, July.
    3. Guanhua Fang & Jingchen Liu & Zhiliang Ying, 2019. "On the Identifiability of Diagnostic Classification Models," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 19-40, March.
    4. Chen, Yunxiao & Liu, Jingchen & Xu, Gongjun & Ying, Zhiliang, 2015. "Statistical analysis of Q-matrix based diagnostic classification models," LSE Research Online Documents on Economics 103183, London School of Economics and Political Science, LSE Library.

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