A natural way of modelling relative survival through regression analysis is to assume an
additive form between the expected population hazard and the excess hazard due to the …

The goal of relative survival methodology is to compare the survival experience of a cohort
with that of the background population. Most often an additive excess hazard model is …

Relative survival methods permit separating the effects of prognostic factors on disease‐
related 'excess mortality'from their effects on other‐causes 'natural mortality', even when …

Four approaches to estimating a regression model for relative survival using the method of
maximum likelihood are described and compared. The underlying model is an additive …

The short‐term and long‐term hazard ratio model includes the proportional hazards model
and the proportional odds model as submodels, and allows a wider range of hazard ratio …

In contrast to the proportional hazards model, the additive risk model specifies that the
hazard function associated with a set of possibly time-varying covariates is the sum of, rather …

One majoraspect in medical research is to relate the survival times ofpatients with the
relevant covariates or explanatory variables. The proportional hazards model has been …

Regression models for survival data are often specified from the hazard function while
classical regression analysis of quantitative outcomes focuses on the mean value (possibly …

Background Statistical analysis of lifetime data is frequently used in the biomedical area. Our
objective was to present a comparative review of the different regression models according …

In survival analysis we are interested in time from the beginning of an observation until
certain event (death, relapse, etc.). We assume that the final event is well defined, so that we …