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rdf:type |
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lifeskim:mentions |
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pubmed:issue |
3
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pubmed:dateCreated |
1998-11-3
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pubmed:abstractText |
In longitudinal random effects models, the random effects are typically assumed to have a normal distribution in both Bayesian and classical models. We provide a Bayesian model that allows the random effects to have a nonparametric prior distribution. We propose a Dirichlet process prior for the distribution of the random effects; computation is made possible by the Gibbs sampler. An example using marker data from an AIDS study is given to illustrate the methodology.
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pubmed:grant |
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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|
pubmed:chemical |
|
|
pubmed:status |
MEDLINE
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pubmed:month |
Sep
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|
pubmed:issn |
0006-341X
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pubmed:author |
|
|
pubmed:issnType |
Print
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pubmed:volume |
54
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
921-38
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pubmed:dateRevised |
2007-11-15
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pubmed:meshHeading |
pubmed-meshheading:9750242-Acquired Immunodeficiency Syndrome,
pubmed-meshheading:9750242-Anti-HIV Agents,
pubmed-meshheading:9750242-Bayes Theorem,
pubmed-meshheading:9750242-Biometry,
pubmed-meshheading:9750242-CD4 Lymphocyte Count,
pubmed-meshheading:9750242-Clinical Trials as Topic,
pubmed-meshheading:9750242-Didanosine,
pubmed-meshheading:9750242-Longitudinal Studies,
pubmed-meshheading:9750242-Models, Statistical,
pubmed-meshheading:9750242-Randomized Controlled Trials as Topic,
pubmed-meshheading:9750242-Zidovudine
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pubmed:year |
1998
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|
pubmed:articleTitle |
A semiparametric Bayesian approach to the random effects model.
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pubmed:affiliation |
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
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pubmed:publicationType |
Journal Article,
Research Support, U.S. Gov't, P.H.S.
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