Period analysis is increasingly employed in analyses of long-term survival of patients with chronic diseases such as cancer, as it derives more up-to-date survival estimates than traditional cohort based approaches. It has recently been extended with regression modelling using generalized linear models, which increases the precision of the survival estimates and enables to assess and account for effects of additional covariates. This paper provides a detailed presentation how model based period analysis may be used to derive population-based absolute and relative survival estimates using the freely available R language and statistical environment and already available R programs for period analysis. After an introduction of the underlying regression model and a description of the software tools we provide a step-by-step implementation of two regression models in R and illustrate how estimates and a test for trend over time in relative survival may be derived using data from a population based cancer registry.
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