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Activity Number:
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331
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, July 31, 2007 : 2:00 PM to 3:50 PM
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Sponsor:
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WNAR
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| Abstract - #309439 |
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Title:
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Joint Analysis of Longitudinal Measurements and Competing Risks Failure Time Data: A Bayesian Approach
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Author(s):
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Wenhua Hu*+ and Gang Li
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Companies:
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University of California, Los Angeles and University of California, Los Angeles
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Address:
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3232 Sawtelle Blvd, Los Angeles, CA, 90066,
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Keywords:
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Competing risks ; joint longitudinal and survival model ; informative censoring ; Bayesian Modeling
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Abstract:
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This paper proposes a Bayesian method for joint modeling of longitudinal and competing risks survival data. The outcomes are modeled by observed covariates as well as by some unobserved factors which introduce latent association between the longitudinal model and competing risks model. This approach is useful in many applications since it allows us to analyze the longitudinal outcome with non-ignorable missing data induced by multiple types of events, to analyze longitudinal and survival data with informative censoring for the key event by treating it as a competing risk, and to model both endpoints simultaneously given both observed covariates and unobserved factors. We present an analysis for a data set from a clinical trial of the scleroderma lung disease. The performance of our joint modeling approach is evaluated through simulations.
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- Authors who are presenting talks have a * after their name.
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