  In this article, I present the user written stmixed command for the fitting
of multilevel survival models, which serves as both an alternative to Stata's
official mestreg, and a complimentary program with substantial extensions.
stmixed can fit multilevel survival models with any number of levels and random
effects at each level, including flexible spline-based approaches (such as
Royston-Parmar and the log hazard equivalent) or user-defined hazard models.
Simple or complex time-dependent effects can be included, as well as the
addition of expected mortality for a relative survival model.
Left-truncation/delayed entry can be used and t-distributed random effects are
provided as an alternative to Gaussian random effects. 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). stmixed is part of the merlin family (Crowther 2017,
2018).
