GENERIC 10214004

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Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0038952, umls-concept:C0302523, umls-concept:C0542341, umls-concept:C0680844, umls-concept:C0681916, umls-concept:C0700325, umls-concept:C0750572, umls-concept:C1145667, umls-concept:C1167622, umls-concept:C2349209, umls-concept:C2825311
pubmed:issue	1
pubmed:dateCreated	1999-5-18
pubmed:abstractText	Stochastic ordering of survival functions is a useful concept in many areas of statistics, especially in nonparametric and order restricted inferences. In this paper we introduce an algorithm to compute maximum likelihood estimates of survival functions where both upper and lower bounds are given. The algorithm allows censored survival data. In a simulation study, we found that the proposed estimates are more efficient than the unrestricted Kaplan-Meier product limit estimates both with and without censored observations.
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/9516348
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:issn	1380-7870
pubmed:author	pubmed-author:LeaC ECE, pubmed-author:ShiN ZNZ, pubmed-author:YauSS
pubmed:issnType	Print
pubmed:volume	5
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	81-90
pubmed:dateRevised	2006-11-15
pubmed:meshHeading	pubmed-meshheading:10214004-Algorithms, pubmed-meshheading:10214004-Computer Simulation, pubmed-meshheading:10214004-Statistics, Nonparametric, pubmed-meshheading:10214004-Stochastic Processes, pubmed-meshheading:10214004-Survival Analysis
pubmed:year	1999
pubmed:articleTitle	Nonparametric estimation of bounded survival functions with censored observations.
pubmed:affiliation	Department of Mathematics and Statistics, Memorial University of Newfoundland, St. John's, Canada.
pubmed:publicationType	Journal Article, Research Support, Non-U.S. Gov't