Kernel smoothing of Aalen's linear regression model

The linear regression model by Aalen for failure time analysis
allows the inclusion of time-dependent covariates as well as the
variation of covariate effects over time. For estimation Aalen
considers cumulative hazard functions and derives estimates by
applying counting process theory. Since often hazard functions
themselves are of primary interest rather than cumulative hazard
functions, in this paper we consider kernel estimation of the
hazard functions, particularly in the presence of time-dependent
covariates. Different kinds of bandwidths and kernel functions are
discussed. A comparison of the considered methods is illustrated by
data from the Stanford Heart Transplant Study.