Source:http://linkedlifedata.com/resource/pubmed/id/21225894
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rdf:type | |
lifeskim:mentions | |
pubmed:issue |
4
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pubmed:dateCreated |
2011-1-12
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pubmed:abstractText |
We introduce a new approach to inference for subgroups in clinical trials. We use Bayesian model selection, and a threshold on posterior model probabilities to identify subgroup effects for reporting. For each covariate of interest, we define a separate class of models, and use the posterior probability associated with each model and the threshold to determine the existence of a subgroup effect. As usual in Bayesian clinical trial design we compute frequentist operating characteristics, and achieve the desired error probabilities by choosing an appropriate threshold(s) for the posterior probabilities.
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pubmed:grant | |
pubmed:language |
eng
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pubmed:journal | |
pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:month |
Feb
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pubmed:issn |
1097-0258
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pubmed:author | |
pubmed:copyrightInfo |
2010 John Wiley & Sons, Ltd.
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pubmed:issnType |
Electronic
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pubmed:day |
20
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pubmed:volume |
30
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
312-23
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pubmed:meshHeading | |
pubmed:year |
2011
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pubmed:articleTitle |
A Bayesian subgroup analysis with a zero-enriched Polya Urn scheme.
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pubmed:affiliation |
Department of Mathematical Science, University of Cincinnati, Cincinnati, OH 45221-0025, U.S.A. sivagas@ucmail.uc.edu
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pubmed:publicationType |
Journal Article
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