12413241

Source:http://linkedlifedata.com/resource/pubmed/id/12413241

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Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0008976, umls-concept:C0013135, umls-concept:C0205127, umls-concept:C0679199, umls-concept:C0936012, umls-concept:C1523987, umls-concept:C1707455
pubmed:issue	2
pubmed:dateCreated	2002-11-4
pubmed:abstractText	Patients may withdraw from longitudinal clinical trials for many reasons. Methods for handling the problem presented by missing data of patients who withdraw before reaching the time point of the primary measurement include carrying the last observation forward (LOCF), data as observed analysis (DAO), mixed model approaches, and pattern mixture models.
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/9200436
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:month	May
pubmed:issn	1054-3406
pubmed:author	pubmed-author:GouldA LawrenceAL, pubmed-author:LiuGuanghanG
pubmed:issnType	Print
pubmed:volume	12
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	207-26
pubmed:dateRevised	2007-11-15
pubmed:meshHeading	pubmed-meshheading:12413241-Analysis of Variance, pubmed-meshheading:12413241-Clinical Trials as Topic, pubmed-meshheading:12413241-Humans, pubmed-meshheading:12413241-Longitudinal Studies, pubmed-meshheading:12413241-Patient Dropouts
pubmed:year	2002
pubmed:articleTitle	Comparison of alternative strategies for analysis of longitudinal trials with dropouts.
pubmed:affiliation	Merck Research Laboratories, Pennsylvania, USA. guanghan_frank_liu@merck.com
pubmed:publicationType	Journal Article, Comparative Study