1. A sequential exploratory diagnostic model using a Pólya-gamma data augmentation strategy.
- Author
-
Jimenez A, Balamuta JJ, and Culpepper SA
- Subjects
- Humans, Bayes Theorem, Monte Carlo Method, Markov Chains, Algorithms
- Abstract
Cognitive diagnostic models provide a framework for classifying individuals into latent proficiency classes, also known as attribute profiles. Recent research has examined the implementation of a Pólya-gamma data augmentation strategy binary response model using logistic item response functions within a Bayesian Gibbs sampling procedure. In this paper, we propose a sequential exploratory diagnostic model for ordinal response data using a logit-link parameterization at the category level and extend the Pólya-gamma data augmentation strategy to ordinal response processes. A Gibbs sampling procedure is presented for efficient Markov chain Monte Carlo (MCMC) estimation methods. We provide results from a Monte Carlo study for model performance and present an application of the model., (© 2023 British Psychological Society.)
- Published
- 2023
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