Joint model of recurrent events and a terminal event with time-varying coefficients

Abstract

Joint modeling of recurrent events and a terminal event has been studied extensively in the past decade. However, most of the previous works assumed constant regression coefficients. This paper proposes a joint model with time-varying coefficients in both event components. The proposed model not only accommodates the correlation between the two type of events, but also characterizes the potential time-varying covariate effects. It is especially useful for evaluating long-term risk factors' effect that could vary with time. A Gaussian frailty is used to model the correlation between event times. The nonparametric time-varying coefficients are modeled using cubic splines with penalty terms. A simulation study shows that the proposed estimators perform well. The model is used to analyze the readmission rate and mortality jointly for stroke patients admitted to Veterans Administration (VA) Hospitals.

Keywords: Frailty model; Laplace approximation; Penalize spline; Stroke.