7981401

Source:http://linkedlifedata.com/resource/pubmed/id/7981401

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Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0034980, umls-concept:C0038952, umls-concept:C0205257, umls-concept:C0441712, umls-concept:C1257890, umls-concept:C1511726
pubmed:issue	3
pubmed:dateCreated	1995-1-3
pubmed:abstractText	Previous methods for the analysis of survival data with incomplete covariates have assumed that the missing-data and censoring mechanisms are ignorable. We relax both assumptions for the analysis of grouped survival data.
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/0370625
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:month	Sep
pubmed:issn	0006-341X
pubmed:author	pubmed-author:BakerS GSG
pubmed:issnType	Print
pubmed:volume	50
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	821-6
pubmed:dateRevised	2006-11-15
pubmed:meshHeading	pubmed-meshheading:7981401-Epidemiologic Methods, pubmed-meshheading:7981401-Humans, pubmed-meshheading:7981401-Mathematics, pubmed-meshheading:7981401-Models, Statistical, pubmed-meshheading:7981401-Probability, pubmed-meshheading:7981401-Regression Analysis, pubmed-meshheading:7981401-Survival Analysis, pubmed-meshheading:7981401-Survival Rate
pubmed:year	1994
pubmed:articleTitle	Regression analysis of grouped survival data with incomplete covariates: nonignorable missing-data and censoring mechanisms.
pubmed:affiliation	Biometry Branch, National Cancer Institute, Bethesda, Maryland 20892-7354.
pubmed:publicationType	Journal Article, Comparative Study