Research Article
The design of simulation studies in medical statistics
Article first published online: 31 AUG 2006
DOI: 10.1002/sim.2673
Copyright © 2006 John Wiley & Sons, Ltd.
Issue
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Statistics in Medicine
Special Issue: Papers from the 26th Annual Conference of the International Society for Clinical Biostatistics
Volume 25, Issue 24, pages 4279–4292, 30 December 2006
Additional Information
How to Cite
Burton, A., Altman, D. G., Royston, P. and Holder, R. L. (2006), The design of simulation studies in medical statistics. Statistics in Medicine, 25: 4279–4292. doi: 10.1002/sim.2673
Publication History
- Issue published online: 28 NOV 2006
- Article first published online: 31 AUG 2006
- Manuscript Accepted: 6 JUL 2006
- Manuscript Received: 15 JUN 2006
Funded by
- Cancer Research U.K.
- Abstract
- References
- Cited By
Keywords:
- simulation study;
- design;
- protocol;
- bias;
- mean square error;
- coverage
Abstract
Simulation studies use computer intensive procedures to assess the performance of a variety of statistical methods in relation to a known truth. Such evaluation cannot be achieved with studies of real data alone. Designing high-quality simulations that reflect the complex situations seen in practice, such as in prognostic factors studies, is not a simple process. Unfortunately, very few published simulation studies provide sufficient details to allow readers to understand fully all the processes required to design a simulation study. When planning a simulation study, it is recommended that a detailed protocol be produced, giving full details of how the study will be performed, analysed and reported. This paper details the important considerations necessary when designing any simulation study, including defining specific objectives of the study, determining the procedures for generating the data sets and the number of simulations to perform. A checklist highlighting the important considerations when designing a simulation study is provided. A small review of the literature identifies the current practices within published simulation studies. Copyright © 2006 John Wiley & Sons, Ltd.

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