Fahrmeir, Ludwig; Klinger, Artur
A nonparametric multiplicative hazard model for event history analysis.
Collaborative Research Center 386, Discussion Paper 12
A major issue in exploring and analyzing life history data with multiple states and events is the development and availability of flexible methods that allow simultaneous incorporation and estimation of baseline hazards, detection and modelling of nonlinear functional forms of covariates and time-varying effects, and the possibility to include time-dependent covariates. In this paper we consider a nonparametric multiplicative hazard model that takes into account these aspects. Embedded in the counting process approach, estimation is based on penalized likelihoods and splines. The methods are illustrated by two real data applications, one to a more conventional survival data set with two absorbing states, and one to more complex sleep-electroencephalography data with multiple recurrent states of sleep.