Tools to simulate realistic censored survival-time distributions
Patrick Royston
Hub for Trials Methodology Research
MRC Clinical Trials Unit
and University College London
London, UK
[email protected]
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Abstract. Simulation of realistic censored survival times is challenging. Most
research studies use highly simplified models, such as the exponential, that do not
adequately reflect the patterns of time to event and censoring seen in real datasets.
In this article, I present a general method of simulating such data based on flexible
parametric survival models (Royston and Parmar, 2002, Statistics in Medicine 21:
2175–2197). A key component of the approach is modeling not only the time
to event but also the time to censoring. I illustrate the methods in data from
clinical trials and from a prognostic study. I also describe a new Stata program,
stsurvsim, that does the necessary calculations.
View all articles by this author:
Patrick Royston
View all articles with these keywords:
stsurvsim, survival analysis, Monte Carlo simulation, flexible parametric survival models, time to event, time to censoring, clinical trials
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