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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. [ABSTRACT FROM AUTHOR]

Restless legs syndrome or RLS is a common neurological disorder prevalent in both adults and children and is often detrimental to regulatory sleep processes. RLS is subdivided into primary/idiopathic RLS and secondary RLS that is due to a related medical condition. Risk factors associated with the development of RLS include: pregnancy, iron deficiency, genetic heritability, and Attention Deficit Hyperactivity Disorder (ADHD). Additionally, RLS has high comorbidity with periodic limb movements during sleep (PLMS), insomnia, and nocturnal eating. Iron replacement and behavior therapy can be successful treatment approaches initially; however drug therapy (e.g., dopaminergic agents, opiates, and antiepileptic medications, and benzodiazepine receptor agonists) can be used in severe cases of RLS. The long-term prognosis of idiopathic RLS is not fatal; however, chronic secondary RLS can exacerbate associated medical conditions and present significant health risks. The symptoms of RLS have not been presented as detrimental to individual judgment and/or psyche. Thus, the Court has maintained the position that individuals with RLS are liable for any and all committed offenses. [ABSTRACT FROM AUTHOR]