ArticleFrontiers in psychology2020
Bayesian Estimation of the DINA Model With Pólya-Gamma Gibbs Sampling.
Article in Frontiers in psychology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Bayesian Transition Diagnostic Classification Models with Polya-Gamma Augmentation.Psychometrika · 2025Article
- Supervised diagnostic classification of cognitive attributes using data augmentation.PloS one · 2024Article
- Exploratory Restricted Latent Class Models with Monotonicity Requirements under PÒLYA-GAMMA Data Augmentation.Psychometrika · 2022Article
- Modeling Not-Reached Items in Cognitive Diagnostic Assessments.Frontiers in psychology · 2022Article
- Bayesian Analysis of Aberrant Response and Response Time Data.Frontiers in psychology · 2022Article
- Estimating CDMs Using the Slice-Within-Gibbs Sampler.Frontiers in psychology · 2020Article
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4 authors.
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Abstract
With the increasing demanding for precision of test feedback, cognitive diagnosis models have attracted more and more attention to fine classify students whether has mastered some skills. The purpose of this paper is to propose a highly effective Pólya-Gamma Gibbs sampling algorithm (Polson et al., 2013) based on auxiliary variables to estimate the deterministic inputs, noisy "and" gate model (DINA) model that have been widely used in cognitive diagnosis study. The new algorithm avoids the Metropolis-Hastings algorithm boring adjustment the turning parameters to achieve an appropriate acceptance probability. Four simulation studies are conducted and a detailed analysis of fraction subtraction data is carried out to further illustrate the proposed methodology.
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