Abstract Details
Activity Number:
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489
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 6, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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International Chinese Statistical Association
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Abstract #311195
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View Presentation
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Title:
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Regression Extension of the Win Ratio Approach for Composite Endpoints with Clinical Priorities
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Author(s):
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Xiaodong Luo*+ and Ken Cheung and Wei Yann Tsai
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Companies:
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Mount Sinai School of Medicine and Columbia University and Columbia University
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Keywords:
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win ratio ;
composite endpoints ;
proportional hazards model ;
regression extension
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Abstract:
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In two-sample case, Pocock et al. (2012) proposed a win ratio approach to analyze composite endpoints consisting of both fatal and non-fatal outcomes with different clinical priorities, and Luo et al. (2014) derived the null hypothesis and proposed a closed-form variance estimator for the win ratio statistic. In this talk, we propose a proportional-hazards-type regression model to extend the win ratio approach. We will also propose and compare three estimation methods for such model: Gehan, Hybrid and Log-rank, and found that the Log-rank method will provide best precision through empirical and theoretical studies.
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Authors who are presenting talks have a * after their name.
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