The Stata Journal (2013) vv, Number ii, pp. 1–25 Estimating and modelling relative survival

Abstract. Relative survival, the survival analogue of excess mortality, is the method of choice for estimating patient survival using data collected by population-based cancer registries. The relative survival ratio is typically estimated from life tables as the ratio of the observed survival of the patients (where all deaths are considered events) to the expected survival of a comparable group from the general population. This article describes the command strs for life table estimatation of relative survival. Three methods of estimating expected survival are available and estimates can be made using a cohort, period, or hybrid approach. A life table version of the Pohar Perme estimator of net survival is also available. Two methods for age standardisation are available. Probabilities of death due to cancer and due to other causes can be estimated using the method of Cronin and Feuer. Excess mortality can be modelled using a range of approaches including full likelihood (using the ml command) and Poisson regression (using the glm command with a user-specified link function)