Linked Life Data

11550948

Source:http://linkedlifedata.com/resource/pubmed/id/11550948

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2001-9-11
pubmed:abstractText
The problem of testing a dose-response relationship in the presence of exchangeably correlated binary data has been addressed using a variety of models. Most commonly used approaches are derived from likelihood or generalized estimating equations and rely on large-sample theory to justify their inferences. However, while earlier work has determined that these methods may perform poorly for small or sparse samples, there are few alternatives available to those faced with such data. We propose an exact trend test for exchangeably correlated binary data when groups of correlated observations are ordered. This exact approach is based on an exponential model derived by Molenberghs and Ryan (1999) and Ryan and Molenberghs (1999) and provides natural analogues to Fisher's exact test and the binomial trend test when the data are correlated. We use a graphical method with which one can efficiently compute the exact tail distribution and apply the test to two examples.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0006-341X
pubmed:author
pubmed:issnType
Print
pubmed:volume
57
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
941-8
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
An exact trend test for correlated binary data.
pubmed:affiliation
Department of Mathematics and Statistics, Utah State University, Logan 84322-3900, USA. corcoran@math.usu.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.