Source:http://linkedlifedata.com/resource/pubmed/id/10748794
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
2
|
| pubmed:dateCreated |
2000-4-28
|
| pubmed:abstractText |
Cohort studies allow an exploration of patient change over time. They can provide information on the incidence of disease, prognosis (including patient satisfaction) and likely health-care resource use. Nonetheless, bias can be present in cohort studies in the way patients are selected and followed-up, the way measures are taken, or the way data are analysed. This short paper explores ways in which such flaws can be uncovered in published studies, so that their findings can be interpreted appropriately.
|
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:status |
MEDLINE
|
| pubmed:month |
Feb
|
| pubmed:issn |
1462-3935
|
| pubmed:author | |
| pubmed:issnType |
Print
|
| pubmed:volume |
61
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
133-5
|
| pubmed:dateRevised |
2000-12-18
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| pubmed:meshHeading | |
| pubmed:year |
2000
|
| pubmed:articleTitle |
Bias in cohort studies.
|
| pubmed:affiliation |
Department of Management, University of St Andrews, Fife.
|
| pubmed:publicationType |
Journal Article
|