survsim

survsim

Simulating time-to-event data from parametric distributions, custom distributions, competing risk models and general multi-state models

Latest stable release: v4.0.9

survsim provides a cutting-edge framework for simulation of survival data. It allows simulation of survival data from a parametric distribution, a custom/user-defined distribution, from a fitted merlin model, from a specified cause-specific hazards competing risks model, or from a specified general multi-state model (with multiple timescales). Left truncation (delayed entry) is now also available for all settings.

For an introductory seminar, see “Simulating time-to-event data from parametric distributions, custom distributions, competing risk models and general multi-state models”.


Installation

The latest stable version of survsim is available on the Statistical Software Components archive, and can be installed directly in Stata by typing:

ssc install survsim

Posts
Simulation and estimation of three-level survival models: IPD meta-analysis of recurrent event data
In this example I'll look at the analysis of clustered survival data …
Survival analysis with interval censoring
Interval censoring occurs when we don't know the exact time an event …
Joint longitudinal and competing risks models: Simulation, estimation and prediction
This post takes a look at an extension of the standard joint …
Simulating survival data with a continuous time-varying covariate…the right way
In this post we'll take a look at how to simulate survival …

Publications

Crowther MJ. Simulating time-to-event data from parametric distributions, custom distributions, competing risk models and general multi-state models. The Stata Journal 2022; 22(1):3-24.

Crowther MJ, Lambert PC. Simulating biologically plausible complex survival data. Statistics in Medicine 2013;32(23):4118-4134.

Crowther MJ, Lambert PC. Simulating complex survival data. The Stata Journal 2012;12(4):674-687.

Red Door Analytics AB is a registered company in Sweden

CEO: Michael Crowther
Org. number: 559351-8359