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Activity Number:
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95
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Type:
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Topic Contributed
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Date/Time:
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Monday, July 30, 2007 : 8:30 AM to 10:20 AM
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Sponsor:
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ENAR
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| Abstract - #309423 |
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Title:
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Methods for Modeling the Recurrent Event Mean in the Presence of Time-Varying Covariates and Time-Dependent Effects
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Author(s):
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Douglas Schaubel*+
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Companies:
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University of Michigan
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Address:
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Department of Biostatistics, Ann Arbor, MI, 48109-2029,
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Keywords:
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censoring ; conditional rate ; marginal mean ; non-proportionality ; survival analysis ; terminating event
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Abstract:
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We consider the setting where the event of interest is recurrent and subject to being terminated. In addition, the treatment and treatment effect are time-dependent. Often in the presence of time-dependent effects, interest lies not in the instantaneous treatment effect, but in the treatment's cumulative effect. We propose semiparametric methods for comparing treatment-specific marginal recurrent event means. The proposal involves combining treatment-specific semiparametric mean function estimators; each of which combines the survival and conditional recurrent event rate function. Large-sample properties are derived and evaluated in finite samples through simulation. The proposed methods are applied to national kidney failure data to estimate the time beyond which the benefit of kidney transplantation is realized with respect to medical cost.
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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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