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Activity Number:
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561
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Type:
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Contributed
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Date/Time:
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Thursday, August 6, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #305352 |
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Title:
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Survival Function with Informative Drop-Outs: Using FGM Copula
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Author(s):
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Md Monir Hossain*+ and Tosiya S. Sato and Mohammad H. Rahbar
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Companies:
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The University of Texas Health Science Center at Houston and Kyoto University and The University of Texas Health Science Center at Houston
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Address:
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6410 Fannin Street, Houston, TX, 77030,
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Keywords:
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survival function ; copula ; FGM bivariate family ; sensitivity
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Abstract:
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The underpinning assumption of independence of failure time and drop-out time is not well supported in many clinical or epidemiological studies. As a consequence, the marginal survival functions are not identifiable. In such a situation, many authors have proposed bounds for the survival functions to check the sensitivity of the estimates to the independence assumption. In this paper, we propose an alternative methodology by adopting an underlying selection process to account for this dependency. We use the Farlie-Gumbel-Morgenstern (FGM) bivariate family for the joint distribution of survival time and the selection variable and then, derive the conditional distribution of the survival time given that it is observed and show how, given the association parameter the survival estimates can be obtained. Here the covariance parameter governs the informativeness of the drop-out process.
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