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Abstract Details
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Activity Number:
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82
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Type:
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Contributed
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Date/Time:
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Sunday, July 31, 2011 : 4:00 PM to 5:50 PM
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Sponsor:
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ENAR
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| Abstract - #301047 |
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Title:
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Joint Modeling of Nonignorable Missing Binary Longitudinal Response and Time-to-Event Data
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Author(s):
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Abdus Sattar*+
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Companies:
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Case Western Reserve University
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Address:
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13302 Cormere Ave, Apt 405, Cleveland , OH, 44120,
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Keywords:
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nonignorable missing ;
longitudinal data ;
survival data ;
pseudo likelihood method ;
inverse probability weighting ;
generalized linear mixed model
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Abstract:
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In many clinical trials binary longitudinal response and time-to-event data are collected from the same individuals. Often longitudinal responses are missing due to subject's dropouts from the study, deaths, etc resulting in non-ignorable missing data. We will analyze non-ignorable missing binary longitudinal response and time-to-event data using weighted pseudo likelihood theory. The weights will be computed via inverse probability augmented methods to account for the non-ignorable missingness. Results from the simulation study will be presented to measure performance of the proposed method. We will also apply this method to a real data set.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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