Linked Life Data

12720255

Source:http://linkedlifedata.com/resource/pubmed/id/12720255

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2003-4-29
pubmed:abstractText
When collecting patient-level resource use data for statistical analysis, for some patients and in some categories of resource use, the required count will not be observed. Although this problem must arise in most reported economic evaluations containing patient-level data, it is rare for authors to detail how the problem was overcome. Statistical packages may default to handling missing data through a so-called 'complete case analysis', while some recent cost-analyses have appeared to favour an 'available case' approach. Both of these methods are problematic: complete case analysis is inefficient and is likely to be biased; available case analysis, by employing different numbers of observations for each resource use item, generates severe problems for standard statistical inference. Instead we explore imputation methods for generating 'replacement' values for missing data that will permit complete case analysis using the whole data set and we illustrate these methods using two data sets that had incomplete resource use information.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1057-9230
pubmed:author
pubmed:copyrightInfo
Copyright 2002 John Wiley & Sons, Ltd.
pubmed:issnType
Print
pubmed:volume
12
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
377-92
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Missing... presumed at random: cost-analysis of incomplete data.
pubmed:affiliation
Health Economics Research Centre, University of Oxford, Institute of Health Sciences, Headington, UK. andrew.biggs@ihs.oc.ac.uk
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't