Latent Partially Ordered Classification Models and Normal Mixtures

Curtis Tatsuoka, Ferenc Varadi and Judith Jaeger
Additional contact information
Curtis Tatsuoka: Department of Neurology, Case Western Reserve University
Ferenc Varadi: Tanar Software
Judith Jaeger: Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine

Journal of Educational and Behavioral Statistics, 2013, vol. 38, issue 3, 267-294

Abstract: Latent partially ordered sets (posets) can be employed in modeling cognitive functioning, such as in the analysis of neuropsychological (NP) and educational test data. Posets are cognitively diagnostic in the sense that classification states in these models are associated with detailed profiles of cognitive functioning. These profiles allow for deeper insight into how functioning can be affected by neurological conditions or by interventions that impact cognition or learning. Responses to NP measures or test items are used as a basis for classification. A natural and useful extension for response models that can be employed in cognitively diagnostic modeling is the implementation of nonparametric density estimation methods. For instance, an issue with NP assessment data is that complex response distributions can arise, such as for populations that are in part comprised of cognitively impaired subjects. To model such complexity, a Dirichlet process prior approach to Bayesian nonparametric density estimation for latent poset models is described. These methods are demonstrated with an analysis of NP data from a study of schizophrenia.

Keywords: partially ordered sets; cognitive diagnosis; nonparametric density estimation; Dirichlet process; neuropsychological assessment (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://journals.sagepub.com/doi/10.3102/1076998612458318 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:38:y:2013:i:3:p:267-294

DOI: 10.3102/1076998612458318

Access Statistics for this article

More articles in Journal of Educational and Behavioral Statistics
Bibliographic data for series maintained by SAGE Publications ().