Document Detail


Coherent psychometric modelling with Bayesian nonparametrics.
MedLine Citation:
PMID:  17903345     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In this paper we argue that model selection, as commonly practised in psychometrics, violates certain principles of coherence. On the other hand, we show that Bayesian nonparametrics provides a coherent basis for model selection, through the use of a 'nonparametric' prior distribution that has a large support on the space of sampling distributions. We illustrate model selection under the Bayesian nonparametric approach, through the analysis of real questionnaire data. Also, we present ways to use the Bayesian nonparametric framework to define very flexible psychometric models, through the specification of a nonparametric prior distribution that supports all distribution functions for the inverse link, including the standard logistic distribution functions. The Bayesian nonparametric approach provides a coherent method for model selection that can be applied to any statistical model, including psychometric models. Moreover, under a 'non-informative' choice of nonparametric prior, the Bayesian nonparametric approach is easy to apply, and selects the model that maximizes the log likelihood. Thus, under this choice of prior, the approach can be extended to non-Bayesian settings where the parameters of the competing models are estimated by likelihood maximization, and it can be used with any psychometric software package that routinely reports the model log likelihood.
Authors:
George Karabatsos; Stephen G Walker
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Publication Detail:
Type:  Journal Article     Date:  2007-09-27
Journal Detail:
Title:  The British journal of mathematical and statistical psychology     Volume:  62     ISSN:  0007-1102     ISO Abbreviation:  Br J Math Stat Psychol     Publication Date:  2009 Feb 
Date Detail:
Created Date:  2009-02-11     Completed Date:  2009-05-11     Revised Date:  2009-11-11    
Medline Journal Info:
Nlm Unique ID:  0004047     Medline TA:  Br J Math Stat Psychol     Country:  England    
Other Details:
Languages:  eng     Pagination:  1-20     Citation Subset:  IM    
Affiliation:
College of Education, University of Illinosis-Chicago, 60607, USA. georgek@uic.edu
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MeSH Terms
Descriptor/Qualifier:
Attitude to Death
Bayes Theorem*
Humans
Models, Statistical*
Psychometrics / statistics & numerical data*
Questionnaires
Statistics, Nonparametric*
Students, Medical / psychology
Terminal Care / psychology

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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