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 techniques are used to compare survival experience in a study cohort with
that expected if background population rates apply. The techniques are especially useful …

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 …

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 …

Relative survival techniques are used to compare the survival experience in a study cohort
with the one expected should they follow the background population mortality rates. The …

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 …

Regression‐based relative survival models are commonly used in population‐based cancer
studies to estimate the real impact on the excess mortality of covariates that influence overall …

Survival estimates are an essential compliment to multivariable regression models for time-
to-event data, both for prediction and illustration of covariate effects. They are easily …

A common goal in the analysis of the long-term survival related to a specific disease is to
estimate a measure that is comparable between populations with different general …

Relative survival is used to estimate patient survival excluding causes of death not related to
the disease of interest. Rather than using cause of death information from death certificates …