Joint Modelling of Recurrent Events with Longitudinal Covariate Using Generalized Gamma Frailty(1/2)

Project Details


Joint modeling approaches have been successfully employed to analyze both survival and longitudinal processes and to investigate their association. Early attention of the approach has been paid on flexible longitudinal processes and adaptive survival process. Recently, the joint modelling approach has been implemented to analyze recurrent events with longitudinal biomarkers. However, for recurrent events data, the survival component in existing joint model mostly chooses the Cox proportional hazards model, which fails proportionality assumption in many cases. Moreover, the shared frailty is usually employed to explain the correlation between recurrent events which is difficult to verify its distribution. Consequently, the project will develop a new joint modelling approach to accommodate flexible survival model and generalized frailty distribution to overcome above difficulties. The extended hazard model is considered as the survival model which contains the Cox and the AFT model as its special cases. The generalized gamma distribution is used as the frailty which contains a few popular frailties, Weibull, lognormal, gamma, and positive stable distribution, as its special cases. An MCEM procedure for pseudo-likelihood function as well as the corresponding asymptotics will be developed for the parameter estimation.
Effective start/end date1/08/1531/07/16

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 5 - Gender Equality
  • SDG 13 - Climate Action
  • SDG 17 - Partnerships for the Goals


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