Linked Life Data

3962972

Source:http://linkedlifedata.com/resource/pubmed/id/3962972

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
1986-5-5
pubmed:abstractText
An increasing number of epidemiologic studies of rare diseases are being conducted as collaborative ventures among several institutions in different geographic areas. Geographic area must be accounted for in the analysis, along with age and other potential confounders. This paper shows that it may not be possible to accurately predict the distribution of persons with rare diseases by age and geographic area. Therefore, selecting controls by matching on age group and geographic area is more efficient than selecting controls in all age and geographic area strata based on prior estimates of expected numbers of cases.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
0002-9262
pubmed:author
pubmed:issnType
Print
pubmed:volume
123
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
901-4
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1986
pubmed:articleTitle
Efficient selection of controls for multi-centered collaborative studies of rare diseases.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.