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Tools to simulate realistic censored survival-time distributions

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  • Patrick Royston

    (MRC Clinical Trials Unit)

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 http://www.stata-journal.com/software/a new Stata program, stsurvsim, that does the necessary calculations. Copyright 2012 by StataCorp LP.

Suggested Citation

  • Patrick Royston, 2012. "Tools to simulate realistic censored survival-time distributions," Stata Journal, StataCorp LLC, vol. 12(4), pages 639-654, December.
    • Handle: RePEc:tsj:stataj:v:12:y:2012:i:4:p:639-654
    Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj12-4/st0274/
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    References listed on IDEAS

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    1. Patrick Royston & Gareth Ambler, 1999. "Multivariable fractional polynomials," Stata Technical Bulletin, StataCorp LLC, vol. 8(43).
    2. Patrick Royston & Willi Sauerbrei, 2009. "Bootstrap assessment of the stability of multivariable models," Stata Journal, StataCorp LLC, vol. 9(4), pages 547-570, December.
    3. Patrick Royston & Paul C. Lambert, 2011. "Flexible Parametric Survival Analysis Using Stata: Beyond the Cox Model," Stata Press books, StataCorp LLC, number fpsaus, March.
    4. Paul C. Lambert & Patrick Royston, 2009. "Further development of flexible parametric models for survival analysis," Stata Journal, StataCorp LLC, vol. 9(2), pages 265-290, June.
    5. W. Sauerbrei & P. Royston, 1999. "Building multivariable prognostic and diagnostic models: transformation of the predictors by using fractional polynomials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(1), pages 71-94.
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    Cited by:

    1. Michael J. Crowther, 2014. "Simulating simple and complex survival data," United Kingdom Stata Users' Group Meetings 2014 06, Stata Users Group.

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