Non-Smooth Backfitting for Excess Risk Additive Regression Model with Two Survival Time-Scales

Abstract: We present a new backfitting algorithm estimating the complex structured non-parametric survival model of Scheike (2001) without having to use smoothing. The considered model is a non-parametric survival model with two time-scales that are equivalent up to a constant that varies over the subjects. Covariate effects are modelled linearly on each time scale by additive Aalen models. Estimators of the cumulative intensities on the two time-scales are suggested by solving local estimating equations jointly on the two time-scales. We are able to estimate the cumulative intensities solving backfitting estimating equations without using smoothing methods and we provide large sample properties and simultaneous confidence bands. The model is applied to data on myocardial infarction providing a separation of the two effects stemming from time since diagnosis and age.