Penalized spline smoothing in multivariable survival models with varying coefficients

The paper discusses penalised spline (P -spline) smoothing for hazard regression of multivariable survival data. Non-proportional hazard functions are fitted in a numerically handy manner by employing Poisson regression which results from numerical integration of the cumulative hazard function. Multivariate smoothing parameters are selected by utilizing the connection between P -spline smoothing and Generalised Linear Mixed Models. A hybrid routine is suggested which combines the Mixed Model idea with a classical Akaike information criteria. The model is evaluated with simulations and applied to data on the success and failure of newly founded companies.