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Activity Number:
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603
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Type:
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Contributed
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Date/Time:
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Thursday, August 6, 2009 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Risk Analysis
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| Abstract - #305111 |
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Title:
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A Proportional Hazards Regression Model for the Subdistribution with Right-Censored and Left-Truncated Competing Risks Data
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Author(s):
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Xu Zhang*+ and Mei-Jie Zhang and Jason Fine
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Companies:
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Georgia State University and Medical College of Wisconsin and The University of North Carolina at Chapel Hill
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Address:
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750 COE, 7th floor, 30 Pryor St, Atlanta, GA, 30303,
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Keywords:
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Competing risks ; Proportional hazards model ; Cumulative incidence function ; Subdistribution
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Abstract:
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In medical studies one often needs to analyze the competing risks data and to assess covariate effects on cumulative incidence probabilities. Fine and Gray (1999) proposed a proportional regression model to directly model the subdistribution of a competing risk and developed the estimating procedures utilizing inverse probability of censoring weighting for right censored only data. Right censored and left truncated competing risks data sometimes occur in biomedical researches. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with right censored and left truncated data. We use a new weighting technique to implement such a model. Inference procedures are developed and the large sample properties of the proposed estimators are derived. For illustration, we analyze a data set from clinical records of children with acute leukemia.
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