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Diagnosis and Prediction pp 91–108Cite as

Bayesian Interim Analysis of Weibull Regression Models with Gamma Frailty

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Part of the book series: The IMA Volumes in Mathematics and its Applications ((IMA,volume 114))

Abstract

This paper considers the problem of planning prospective clinical studies where the primary endpoint is a terminal event and the response variable is a survival time. It is assumed that the lifetimes of the individuals in the study display extra-Weibull variability that causes the usual proportional hazards assumption to fail. The introduction of a Gamma-distributed frailty term to accommodate the between-subject heterogeneity leads to a logarithmic F accelerated failure time model to which the second-order expansions of Papandonatos & Geisser [1] can be applied. The predictive simulation approach of Papandonatos & Geisser [2] can then be used to evaluate the length of the study period needed for a Bayesian hypothesis testing procedure to achieve a conclusive result.

Work supported in part by NSF grant SCREMS-9627804.

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Author information

Authors and Affiliations

  1. Department of Statistics, State University of New York at Buffalo, Buffalo, NY, 14214-3000, USA

    George D. Papandonatos

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  1. George D. Papandonatos
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Editors and Affiliations

  1. School of Statistics, University of Minnesota, Minneapolis, MN, 55455-0436, USA

    Seymour Geisser

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© 1999 Springer Science+Business Media New York

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Papandonatos, G.D. (1999). Bayesian Interim Analysis of Weibull Regression Models with Gamma Frailty. In: Geisser, S. (eds) Diagnosis and Prediction. The IMA Volumes in Mathematics and its Applications, vol 114. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1540-0_6

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  • DOI: https://doi.org/10.1007/978-1-4612-1540-0_6

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-7184-0

  • Online ISBN: 978-1-4612-1540-0

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