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Abstract Details
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Activity Number:
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576
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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| Abstract - #306774 |
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Title:
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Nonparametric Estimation of Hazard in Presence of Dependent Censoring
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Author(s):
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Desale Habtzghi*+ and Somnath Datta
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Companies:
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University of Akron and University of Louisville
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Address:
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302 Buchtel Mall, Akron, OH, 44325, United States
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Keywords:
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Dependent censoring ;
Hazard function ;
Lifetime ;
Shape restriction
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Abstract:
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The hazard function has an important role in modeling lifetime data. It is useful to estimate the hazard function by constraining its shape; based on the empirical or theoretical qualitative information about the hazard function. In this paper we propose nonparametric estimation methods in which the likelihood is maximized over a set of shape-restricted regression for dependent censoring data. We evaluate the performance of our method via simulated studies and illustrate it on real data set.
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Authors who are presenting talks have a * after their name.
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