Linked Life Data

21199689

Source:http://linkedlifedata.com/resource/pubmed/id/21199689

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2011-4-1
pubmed:abstractText
We develop a Bayesian approach for calculating sample sizes for clinical trials under the framework of hypothesis tests. We extend the work of Weiss (The Statistician 1997; 46: 185-191) to include composite distributions for the treatment effect and the variance of the data within the null and alternative hypotheses. We select sample sizes using the Bayes factor and the averaged type I error and type II error defined by Weiss (The Statistician 1997; 46: 185-191). Our approach allows the uncertainty inherent in eliciting prior information for both the treatment effect and the variance and permits informative prior information for unknown quantities through the hypothesis specification. We illustrate our method through a real data example from a clinical trial for treatment of multiple sclerosis and from the cerclage trial for preterm birth prevention in high-risk women.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1559-2030
pubmed:author
pubmed:copyrightInfo
Copyright © 2011 Elsevier Inc. All rights reserved.
pubmed:issnType
Electronic
pubmed:volume
32
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
393-8
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Bayesian sample size determination under hypothesis tests.
pubmed:affiliation
Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35294, USA. xzhang@ms.soph.uab.edu
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't