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A Bayesian Approach to Competing Risks Model with Masked Causes of Failure and Incomplete Failure Times

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submitted on 2023-03-15, 11:50 and posted on 2023-07-12, 11:08 authored by Yosra Yousif, Faiz A. M. Elfaki, Meftah Hrairi, Oyelola A. Adegboye

We present a Bayesian approach for analysis of competing risks survival data with masked causes of failure. This approach is often used to assess the impact of covariates on the hazard functions when the failure time is exactly observed for some subjects but only known to lie in an interval of time for the remaining subjects. Such data, known as partly interval-censored data, usually result from periodic inspection in production engineering. In this study, Dirichlet and Gamma processes are assumed as priors for masking probabilities and baseline hazards. Markov chain Monte Carlo (MCMC) technique is employed for the implementation of the Bayesian approach. The effectiveness of the proposed approach is illustrated with simulated and production engineering applications. 

Other information 

Published in: Mathematical Problems in Engineering
License: http://creativecommons.org/licenses/by/4.0
See article on publisher's website: http://dx.doi.org/10.1155/2020/8248640 

History

Language

  • English

Publisher

Hindawi

Publication Year

  • 2020

Institution affiliated with

  • Qatar University

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