Stata

Description of -stns-, a Stata command that implements the Pohar Perme estimator for discrete survival time data (e.g., life tables).

After fitting a flexible parametric model, we estimate internally age-standardised 5-year survival for males and females for each year of diagnosis.

This page shows code for calculating the Pohar-Perme non-parametric estimate of marginal relative survival using the following four user-written Stata commands. stnet strs stpp stns Code comparing the estimates from strs, stns, stpp, and stns is available for two data sets:

Illustration of stcompadj using the example from the help file

After fitting a flexible parametric model, we estimate and plot the hazard ratio for a covariate that is modified by another covariate.

Illustrates how to fit a model using patient data and then predict in a second dataset specifically constructed to contain only the covariates for which we wish to predict. Age is modelled using a restricted cubic spline.

Creating a second dataset in which to make predictions and an approach to model-based direct age-standardisation.

Illustrates how to fit a model using patient data and then predict in a second dataset specifically constructed to contain only the covariates for which we wish to predict. Age is modelled using a restricted cubic spline.

The code used in this tutorial, along with links to the data, is available here. This code illustrates how to apply the “Brenner alternative approach” to age-standardise net survival using external (ICSS) weights.

We will partition the total effect of sex into the natural indirect effect (mediated by stage) and the natural direct effect. We then illustrate how to estimate the proportion of the sex difference mediated by stage. Emphasis is on illustrating how these quantities can be estimated in Stata using the standsurv command; we won't discuss the neccessary assumptions and their appropriateness.