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ERIC Number: EJ1079855
Record Type: Journal
Publication Date: 2015-Oct
Pages: 23
Abstractor: As Provided
ISSN: ISSN-1076-9986
Bayesian Estimation of the DINA Model with Gibbs Sampling
Culpepper, Steven Andrew
Journal of Educational and Behavioral Statistics, v40 n5 p454-476 Oct 2015
A Bayesian model formulation of the deterministic inputs, noisy "and" gate (DINA) model is presented. Gibbs sampling is employed to simulate from the joint posterior distribution of item guessing and slipping parameters, subject attribute parameters, and latent class probabilities. The procedure extends concepts in Béguin and Glas, Culpepper, and Sahu for estimating the guessing and slipping parameters in the three- and four-parameter normal-ogive models. The ability of the model to recover parameters is demonstrated in a simulation study. The technique is applied to a mental rotation test. The algorithm and vignettes are freely available to researchers as the "dina" R package.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A