Nonparametric Computation of Survival Functions in the Presence of Interval Censoring

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aut.researcherTaylor, Stephen McGregor
dc.contributor.authorTaylor, SM
dc.date.accessioned2011-09-29T01:11:51Z
dc.date.available2011-09-29T01:11:51Z
dc.date.copyright2008-09-01
dc.date.issued2008-09-01
dc.description.abstractCensoring in time-to-event data poses a challenge in survival analysis. General interval censoring places an interval of doubt around each event time. Even when none of the event times are known exactly, useful analysis techniques are available. The nonparametric maximum likelihood (NPMLE) survival function provides a natural way to demonstrate how survival progresses over time. This talk covers recent research using constrained newton methods, mixture distributions and non-negative least squares algorithms to efficiently solve the problem of finding the NPMLE survival function.
dc.identifier.citationPresentation at the New Zealand Statistical Association Conference 2008, Hamilton, New Zealand
dc.identifier.roid12014en_NZ
dc.identifier.urihttps://hdl.handle.net/10292/2158
dc.publisherAUT University
dc.relation.urihttp://stats.org.nz/NZSA2008/index.htm
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dc.rights.accessrightsOpenAccess
dc.titleNonparametric Computation of Survival Functions in the Presence of Interval Censoring
dc.typeConference Contribution
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