Activity Number:
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376
- All Things Bayesian: The Next Generation
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Type:
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Invited
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Date/Time:
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Tuesday, July 30, 2019 : 2:00 PM to 3:50 PM
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Sponsor:
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International Indian Statistical Association
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Abstract #300513
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Presentation
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Title:
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A Practical Bayesian Analysis of Recurrence and Termination
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Author(s):
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Debajyoti Sinha* and Zhixing Xu and Jonathan R. Bradley
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Companies:
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FLORIDA STATE UNIVERSITY and Florida State University and Florida State University
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Keywords:
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Intensity function;
Marginal rate function;
MCMC;
Latent class model
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Abstract:
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When each patient is at risk of recurrent events as well as the terminating event, we present a novel latent-class based semiparametric joint model that offers clinically meaningful and estimable association between the recurrence profile and risk of termination. Unlike previous shared-frailty based joint models, this model has coherent interpretation of the covariate effects on all relevant functions and model quantities that are either conditional or unconditional on events history. We offer a fully Bayesian method for estimation and prediction using a complete specification of the prior process of the baseline functions. Our Markov Chain Monte Carlo tools for both Bayesian methods are implementable via publicly available software. Practical advantages of our methods are illustrated via a simulation study and the analysis of a transplant study with recurrent Non-Fatal Graft Rejections (NFGR) and the termination event of death due to total graft rejection.
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Authors who are presenting talks have a * after their name.