ArticlePsychometrika2023
Bridging Parametric and Nonparametric Methods in Cognitive Diagnosis.
Article in Psychometrika, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 13 citations in OpenAlex.
- Consistency Theory of General Nonparametric Classification Methods in Cognitive Diagnosis.Psychometrika · 2025Article
- Cognitive diagnostic assessment: A Q-matrix constraint-based neural network method.Behavior research methods · 2024Article
- Improving reliability estimation in cognitive diagnosis modeling.Behavior research methods · 2023Article
- A Tensor-EM Method for Large-Scale Latent Class Analysis with Binary Responses.Psychometrika · 2023Article
- Nonparametric cognitive diagnosis of profiles of mathematical knowledge of teacher education candidates.Current psychology (New Brunswick, N.J.) · 2023Article
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A number of parametric and nonparametric methods for estimating cognitive diagnosis models (CDMs) have been developed and applied in a wide range of contexts. However, in the literature, a wide chasm exists between these two families of methods, and their relationship to each other is not well understood. In this paper, we propose a unified estimation framework to bridge the divide between parametric and nonparametric methods in cognitive diagnosis to better understand their relationship. We also develop iterative joint estimation algorithms and establish consistency properties within the proposed framework. Lastly, we present comprehensive simulation results to compare different methods and provide practical recommendations on the appropriate use of the proposed framework in various CDM contexts.
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