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Bayes linear kinematics in a dynamic survival model

Lookup NU author(s): Professor Kevin Wilson, Dr Malcolm Farrow

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Abstract

Bayes linear kinematics and Bayes linear Bayes graphical models provide an extension of Bayes linear methods so that full conditional updates may be combined with Bayes linear belief adjustment. In this paper we investigate the application of this approach to survival analysis with time-dependent covariate effects, a more complicated problem than previous applications. We use a piecewise-constant hazard function with a prior in which covariate effects are correlated over time. The need for computationally intensive methods is avoided and the relatively simple structure facilitates interpretation. Our approach eliminates the problem of non-commutativity which was observed in earlier work by Gamerman. We apply the technique to data on survival times for leukemia patients.

Publication metadata

Author(s): Wilson KJ, Farrow M

Publication type: Article

Publication status: Published

Journal: International Journal of Approximate Reasoning

Year: 2017

Volume: 80

Pages: 239-256

Print publication date: 01/01/2017

Online publication date: 28/09/2016

Acceptance date: 23/09/2016

Date deposited: 27/09/2016

ISSN (print): 0888-613X

ISSN (electronic): 1873-4731

Publisher: Elsevier

URL: http://dx.doi.org/10.1016/j.ijar.2016.09.010

DOI: 10.1016/j.ijar.2016.09.010

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