With the release of Stata 14 came the
mestreg command to fit multilevel mixed effects parametric survival models, assuming normally distributed random effects, estimated with maximum likelihood utilising Gaussian quadrature. In this article, I present the user written
stmixed command, which serves as both an alternative and a complimentary program for the fitting of multilevel parametric survival models, to
mestreg. The key extensions include incorporation of the flexible parametric Royston-Parmar survival model, and the ability to fit multilevel relative survival models. The methods are illustrated with a commonly used dataset of patients with kidney disease suffering recurrent infections, and a simulated example, illustrating a simple approach to simulating clustered survival data using
survsim (Crowther and Lambert, 2012, 2013).