Stata

This page illustrates the algorithm used by strs for estimating relative survival using the Ederer II approach.

Illustrates Stata factor variable notation and how to reparameterise a model to get the estimated effect of an exposure for each level of a modifier. Illustrates how we can fit a single model with interactions that is equivalent to stratified models.

An illustration of how to estimate cumulative incidence functions (CIFs) based on a fitted flexible parametric model

A Comparison of Cox and flexible parametric models with application to studying sex differences in survival of patients diagnosed with melanoma. Illustration of how to plot the time-varying hazard ratio from a flexible parametric model.

In this tutorial, we examine sex difference in survival for patients diagnosed with melanoma and illustrate how to estimate the causal effect of sex on patient survival using regression standardisation (also known and G-Computation). We discuss various approaches to estimating adjusted survival curves and illustrate the meansurv and stpm2_standsurv post-estimation commands to stpm2 (for fitting flexible parametric models in Stata).

Age-standardised net survival using non-parametric methods (Ederer II and Pohar Perme) and ICSS weights.

Estimate conditional (on surviving some time) relative survival using several approaches. We estimate from both life tables and based on a flexible parametric model.

This exercise illustrates an approach to modelling relative survival with missing covariate data using multiple imputation.

Estimation of relative/net survival using four difference approaches (Ederer I, Ederer II, Hakulinen, Pohar Perme)

An illustration of how one can both approximate and exactly replicate estimates from a Cox model using Poisson regression