| Bayesian hierarchical analysis of within-units variances in repeated measures experiments. | |
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MedLine Citation:
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PMID: 7997717 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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We develop hierarchical Bayesian models for biomedical data that consist of multiple measurements on each individual under each of several conditions. The focus is on investigating differences in within-subject variation between conditions. We present both population-level and individual-level comparisons. We extend the partial likelihood models of Chinchilli et al. with a unique Bayesian hierarchical framework for variance components and associated degrees of freedom. We use the Gibbs sampler to estimate posterior marginal distributions for the parameters of the Bayesian hierarchical models. The application involves a comparison of two cholesterol analysers each applied repeatedly to a sample of subjects. Both the partial likelihood and Bayesian approaches yield similar results, although confidence limits tend to be wider under the Bayesian models. |
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Authors:
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T R Ten Have; V M Chinchilli |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Statistics in medicine Volume: 13 ISSN: 0277-6715 ISO Abbreviation: Stat Med Publication Date: 1994 Sep |
Date Detail:
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Created Date: 1995-01-17 Completed Date: 1995-01-17 Revised Date: 2004-11-17 |
Medline Journal Info:
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Nlm Unique ID: 8215016 Medline TA: Stat Med Country: ENGLAND |
Other Details:
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Languages: eng Pagination: 1841-52 Citation Subset: IM |
Affiliation:
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Center for Biostatistics and Epidemiology, Hershey Medical Center, Pennsylvania State University, Hershey 17033. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Bayes Theorem* Blood Chemical Analysis / instrumentation Cholesterol / blood Confidence Intervals Data Interpretation, Statistical Humans Logistic Models* |
| Chemical | |
Reg. No./Substance:
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57-88-5/Cholesterol |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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