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Abstract Details
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Activity Number:
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169
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Type:
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Contributed
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Date/Time:
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Monday, August 1, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #303409 |
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Title:
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Inference for Doubly Censored Data Using Marginal Likelihood
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Author(s):
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Zhiguo Li*+ and Kouros Owzar
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Companies:
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Duke University and Duke University
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Address:
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, , ,
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Keywords:
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doubly censored data ;
marginal likelihood
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Abstract:
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In some applications, the variable of interest is time from a first event to a second event, while both times are interval censored. We propose fitting Cox proportional hazards model to this type of data using marginal likelihood, where the time to first event is integrated out in the empirical likelihood function of the time of interest. This greatly reduces the complexity of the likelihood function compared with the full semiparametric likelihood. The dependence of the time of interest on time to the first event (origin) is induced by including time to the first event as a covariate in the Cox model for the time of interest. Theory for the estimator is established and simulation is conducted to assess its performance. It's also applied to a real data set.
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