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Hierarchical Diagnostic Classification Models Morphing into Unidimensional ‘Diagnostic’ Classification Models—A Commentary

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  • Matthias Davier
  • Shelby Haberman

Abstract

This commentary addresses the modeling and final analytical path taken, as well as the terminology used, in the paper “Hierarchical diagnostic classification models: a family of models for estimating and testing attribute hierarchies” by Templin and Bradshaw (Psychometrika, doi: 10.1007/s11336-013-9362-0 , 2013 ). It raises several issues concerning use of cognitive diagnostic models that either assume attribute hierarchies or assume a certain form of attribute interactions. The issues raised are illustrated with examples, and references are provided for further examination. Copyright The Psychometric Society 2014

Suggested Citation

  • Matthias Davier & Shelby Haberman, 2014. "Hierarchical Diagnostic Classification Models Morphing into Unidimensional ‘Diagnostic’ Classification Models—A Commentary," Psychometrika, Springer;The Psychometric Society, vol. 79(2), pages 340-346, April.
    • Handle: RePEc:spr:psycho:v:79:y:2014:i:2:p:340-346
    DOI: 10.1007/s11336-013-9363-z
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    References listed on IDEAS

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    1. Wim Linden, 2012. "On Compensation in Multidimensional Response Modeling," Psychometrika, Springer;The Psychometric Society, vol. 77(1), pages 21-30, January.
    2. E. Maris, 1999. "Estimating multiple classification latent class models," Psychometrika, Springer;The Psychometric Society, vol. 64(2), pages 187-212, June.
    3. Dean Follmann, 1988. "Consistent estimation in the rasch model based on nonparametric margins," Psychometrika, Springer;The Psychometric Society, vol. 53(4), pages 553-562, December.
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    Cited by:

    1. Jonathan Templin & Laine Bradshaw, 2014. "The Use and Misuse of Psychometric Models," Psychometrika, Springer;The Psychometric Society, vol. 79(2), pages 347-354, April.
    2. Yunxiao Chen & Xiaoou Li & Jingchen Liu & Zhiliang Ying, 2017. "Regularized Latent Class Analysis with Application in Cognitive Diagnosis," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 660-692, September.
    3. Chenchen Ma & Jing Ouyang & Gongjun Xu, 2023. "Learning Latent and Hierarchical Structures in Cognitive Diagnosis Models," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 175-207, March.

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