Application of functional ANOVA models for hazard regression to the Hisayama data

A methodology for modeling covariate effects on the time-to-event data is developed. The covariates are allowed to be time dependent and their effects are modeled using polynomial splines in order to account for possibly non-linear effects. The methodology is applied to examine the effects on the incidence brain infarction based on a cohort study in Hisayama, Japan. The results indicate that at least two non-linear effects are significant (body mass index and systolic blood pressure) and there is a time-varying drug effect. The resulting significant risk factors are assessed by the proposed method that is more flexible and hence less biased than the traditional procedures where linear effects are imposed. These results are extremely important to the local medical investigation. In particular, more insight has been gained by examining the non-linear effects.