17493519

Source:http://linkedlifedata.com/resource/pubmed/id/17493519

Download in:

Switch to

Custom View

Named Graph Language Inference

Statements in which the resource exists as a subject.
Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0242568, umls-concept:C0392756, umls-concept:C0679083, umls-concept:C0679228, umls-concept:C1519941, umls-concept:C1527178, umls-concept:C1705938
pubmed:issue	6
pubmed:dateCreated	2007-5-11
pubmed:abstractText	To evaluate alternative approaches to correct for bias due to inaccurate diagnostic criteria in database studies of associations.
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/8801383
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:month	Jun
pubmed:issn	0895-4356
pubmed:author	pubmed-author:AbrahamowiczMichalM, pubmed-author:Ionescu-IttuRalucaR, pubmed-author:LacailleDianeD, pubmed-author:XiaoYonglingY
pubmed:issnType	Print
pubmed:volume	60
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	600-9
pubmed:dateRevised	2007-11-15
pubmed:meshHeading	pubmed-meshheading:17493519-Arthritis, Rheumatoid, pubmed-meshheading:17493519-Bias (Epidemiology), pubmed-meshheading:17493519-Computer Simulation, pubmed-meshheading:17493519-Confounding Factors (Epidemiology), pubmed-meshheading:17493519-Databases as Topic, pubmed-meshheading:17493519-Diagnostic Errors, pubmed-meshheading:17493519-Disability Evaluation, pubmed-meshheading:17493519-Epidemiologic Methods, pubmed-meshheading:17493519-Female, pubmed-meshheading:17493519-Humans, pubmed-meshheading:17493519-Male, pubmed-meshheading:17493519-Outcome Assessment (Health Care), pubmed-meshheading:17493519-Prognosis
pubmed:year	2007
pubmed:articleTitle	Simulations showed that validation of database-derived diagnostic criteria based on a small subsample reduced bias.
pubmed:affiliation	Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada. Michal@epimgh.mcgill.ca
pubmed:publicationType	Journal Article, Research Support, Non-U.S. Gov't