Source:http://linkedlifedata.com/resource/pubmed/id/18589003
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
5
|
| pubmed:dateCreated |
2008-8-25
|
| pubmed:abstractText |
We propose a Bayesian approach to monitor clinical trials with clustered binary outcomes using multivariate probit models. Our monitoring is based on the calculated probability of the reduced incidence rate using a new treatment compared with the standard treatment greater than a target improvement under different prior scenarios for the treatment effect. We develop a Bayesian sampling algorithm for posterior inference allowing missing values in the outcomes. We illustrate our method using a published early trail of inhaled nitric oxide therapy in premature infants.
|
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:status |
MEDLINE
|
| pubmed:month |
Sep
|
| pubmed:issn |
1559-2030
|
| pubmed:author | |
| pubmed:issnType |
Electronic
|
| pubmed:volume |
29
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
751-5
|
| pubmed:meshHeading |
pubmed-meshheading:18589003-Algorithms,
pubmed-meshheading:18589003-Bayes Theorem,
pubmed-meshheading:18589003-Clinical Trials Data Monitoring Committees,
pubmed-meshheading:18589003-Clinical Trials as Topic,
pubmed-meshheading:18589003-Data Interpretation, Statistical,
pubmed-meshheading:18589003-Humans,
pubmed-meshheading:18589003-Models, Statistical,
pubmed-meshheading:18589003-Multivariate Analysis,
pubmed-meshheading:18589003-Research
|
| pubmed:year |
2008
|
| pubmed:articleTitle |
Bayesian interim analysis in clinical trials.
|
| pubmed:affiliation |
Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, 35294, USA.
|
| pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't
|