Linked Life Data

9160490

Source:http://linkedlifedata.com/resource/pubmed/id/9160490

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
1997-7-17
pubmed:abstractText
Clinical studies that involve the recording of two or more distinct and well-defined events on each subject give rise to multiple event data. Treatment comparisons are usually reported in univariate analyses of time to first event or number of events observed. However, this approach may not uncover the 'full story' of the treatment effect; moreover, it may be inefficient because it does not make full use of the available data. There are a number of published statistical methods for analysing multiple event data. Using data from a real life example, this paper compares the results obtained using the 'older ad hoc' methods with those based on the more recent methods that utilize the multiplicity of the data.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0277-6715
pubmed:author
pubmed:issnType
Print
pubmed:day
30
pubmed:volume
16
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
941-9
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
1997
pubmed:articleTitle
Multiple statistics for multiple events, with application to repeated infections in the growth factor studies.
pubmed:affiliation
Schering-Plough Research Institute, Kenilworth, NJ 07033-0539, USA.
pubmed:publicationType
Journal Article, Clinical Trial, Comparative Study, Randomized Controlled Trial, Multicenter Study, Clinical Trial, Phase III