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A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction


Abu Bakar, Mohd Rizam and A. Salah, Khalid and Ibrahim, Noor Akma and Haron, Kassim (2007) A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction. European Journal of Scientific Research, 18 (4). pp. 707-729. ISSN 1450-216X


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 Cox (1972) 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 nonnegativity of the survival function. A simulation study is presented to evaluate the performance of this joint model.

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Additional Metadata

Item Type: Article
Divisions: Faculty of Science
Publisher: EuroJournals Publishing Inc.
Keywords: Survival model, Longitudinal model, Cure rate model, fixed effects, Randomeffects, Bayesian approach, Integrated Ornstein-Uhlenbeck
Depositing User: Najwani Amir Sariffudin
Date Deposited: 10 Aug 2010 04:55
Last Modified: 08 Dec 2015 09:02
URI: http://psasir.upm.edu.my/id/eprint/7671
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