Stochastic properties of the mixed accelerated hazard models

Ping Li, Xiaoliang Ling and Weiyong Ding

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 13, 6433-6445

Abstract: The accelerated hazard model in survival analysis assumes that the covariate effect acts the time scale of the baseline hazard rate. In this paper, we study the stochastic properties of the mixed accelerated hazard model since the covariate is considered basically unobservable. We build dependence structure between the population variable and the covariate, and also present some preservation properties. Using some well-known stochastic orders, we compare two mixed accelerated hazards models arising out of different choices of distributions for unobservable covariates or different baseline hazard rate functions.

Date: 2017
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DOI: 10.1080/03610926.2015.1129416

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