|
Abstract:
|
Recurrent event data occur in many fields and many approaches have been proposed for their analyses. However, most of the available methods only allow time-independent covariate effects and sometimes this may not be true as, for example, a treatment effect may decrease with time. In this paper, we consider the analysis of multivariate recurrent event data in which some covariate effects may be time-dependent. For the problem, some marginal models for the underlying counting processes are presented and an estimating equation-based inference procedure is presented. The asymptotic properties of the proposed estimates are established and their finite sample properties are evaluated through simulation studies. We also apply the approach to a set of real data.
|
