Source:http://linkedlifedata.com/resource/pubmed/id/16592839
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
6
|
| pubmed:dateCreated |
2010-6-30
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| pubmed:abstractText |
A model for sequential clinical trials is discussed. Three proposed stopping rules are studied by the Monte Carlo method for small patient horizons and mathematically for large patient horizons. They are shown to be about equally effective and asymptotically optimal from both Bayesian and frequentist points of view and are markedly superior to any fixed sample size procedure.
|
| pubmed:commentsCorrections | |
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:status |
PubMed-not-MEDLINE
|
| pubmed:month |
Jun
|
| pubmed:issn |
0027-8424
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| pubmed:author | |
| pubmed:issnType |
Print
|
| pubmed:volume |
77
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
3135-8
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| pubmed:dateRevised |
2010-9-15
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| pubmed:year |
1980
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| pubmed:articleTitle |
Sequential medical trials.
|
| pubmed:affiliation |
Department of Mathematical Statistics, Columbia University, New York, New York 10027.
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| pubmed:publicationType |
Journal Article
|