Nonparametric regression using local kernel estimating equations for correlated failure time data

We study nonparametric regression for correlated failure timedata. Kernel estimating equations are used to estimate nonparametriccovariate effects. Independent and weighted-kernel estimatingequations are studied. The derivative of the nonparametric functionis first estimated and the nonparametric function is then estimatedby integrating the derivative estimator. We show that the nonparametrickernel estimator is consistent for any arbitrary working correlationmatrix and that its asymptotic variance is minimized by assumingworking independence. We evaluate the performance of the proposedkernel estimator using simulation studies, and apply the proposedmethod to the western Kenya parasitaemia data.