Linked Life Data

15209194

Source:http://linkedlifedata.com/resource/pubmed/id/15209194

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2004-6-22
pubmed:abstractText
The frequency of randomized cluster trials is increasing in primary care research. These trials are differentiated by the randomization method, in which a group of individuals is randomly assigned to an intervention as a cluster rather than as individuals. Characteristically, individuals within a cluster tend to be more alike than individuals selected at random. For instance, evaluating the effect of an intervention across medical care providers at an institutional level or at a physician group practice level fits the randomized cluster model. Three examples in this article show how failure to account for the dependence introduced by unit of randomization can affect the analysis of binary data and the conclusions of randomized cluster trials. Greater consideration of the nested nature of patient, physician, and practice data would increase the quality of primary care research.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1544-1709
pubmed:author
pubmed:issnType
Print
pubmed:volume
2
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
201-3
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:articleTitle
Adjusted chi-square statistics: application to clustered binary data in primary care.
pubmed:affiliation
Research Institute, St. Luke's Hospital and Health Network, 801 Ostrum Street, Bethlehem, PA 18015, USA. ReedJ@slhn.org
pubmed:publicationType
Journal Article