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Bayesian approach for joint longitudinal and time-to-event data with survival fraction


Citation

Abu Bakar, Mohd Rizam and Salah, Khalid Ali and Ibrahim, Noor Akma and Haron, Kassim (2009) Bayesian approach for joint longitudinal and time-to-event data with survival fraction. Bulletin of the Malaysian Mathematical Sciences Society, 32 (1). pp. 75-100. ISSN 0126-6705; ESSN: 2180-4206

Abstract

Many medical investigations generate both repeatedly-measured(longitudinal) biomarker and survival data. One of complex issue arises when investigating the association between longitudinal and time-to-event data when there are cured patients in the population, which leads to a plateau in the survival function S(t) after sufficient follow-up. Thus, usual Cox proportional hazard model [11] is not applicable since the proportional hazard assumption is violated. An alternative is to consider survival models incorporating a cure fraction. In this paper, we present a new class of joint model for univariate longitudinal and survival data in presence of cure fraction. For the longitudinal model, a stochastic Integrated Ornstein-Uhlenbeck process will present, and for the survival model a semiparametric survival function will be considered which accommodate both zero and non-zero cure fractions of the dynamic disease progression. Moreover, we consider a Bayesian approach which is motivated by the complexity of the model. Posterior and prior specification needs to accommodate parameter constraints due to the non-negativity of the survival function. A simulation study is presented to evaluate the performance of the proposed joint model.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Science
Institute for Mathematical Research
Publisher: Malaysian Mathematical Sciences Society and Universiti Sains Malaysia
Keywords: Survival model; Longitudinal model; Cure rate model; Fixed effects; Random effects; Bayesian approach; Integrated Ornstein-Uhlenbeck
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 08 Jun 2015 03:22
Last Modified: 19 Nov 2015 08:17
URI: http://psasir.upm.edu.my/id/eprint/13373
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