Quantile estimation of partially varying coefficient model for panel count data with informative observation times

Panel count data frequently arise in various applications such as medical research, social sciences and so on. In this paper, a partially varying coefficient model of the panel count data with informative observation times is developed to accommodate the nonlinear interact effects between covariates. For statistical inference of the unknown parameters, quantile regression approaches are proposed, in which the baseline function and the varying coefficients are approximated by B-spline functions. Moreover, asymptotic properties for the estimators are established. Some numerical studies are performed to confirm and evaluate the finite-sample behaviours of the proposed approaches. Finally, the proposed model is applied to the bladder cancer tumour data as an application.