Abstract
In planning and proposing a study, a paramount concern is the likelihood that the study will provide useful or meaningful information. An important factor in demonstrating that a study will be informative is sample size. If a study has a sub-optimal number of subjects, it may be under-powered to detect statistical significance even in the presence of a true effect, or estimates produced by the study may lack useful precision. On the other hand, if a study has too many subjects, one may encounter resource limitations and ethical issues associated with exposing an unnecessarily large number of subjects to risk. An optimal study size therefore balances the need for adequate statistical power or precision, the limited nature of resources, and the ethical obligation to limit exposure to risk. As such, study proposals and scientific papers often include sections on the planning of study size. This chapter begins with an exploration of various factors that contribute to optimal study size. We then briefly review some useful sample size calculations in the contexts of surveys, cohort studies, case–control studies, and randomized trials.
Validity considerations alone are often sufficient to imply that zero is the optimal size.
Olli S. Miettinen
The online version of the book can be found at http://dx.doi.org/10.1007/978-94-007-5989-3
An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-94-007-5989-3_32
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Altman DG et al (2008) Statistics with confidence, 2nd edn. BMJ Books, London, pp 1–240. ISBN 9780727913753
Bristol DR (1989) Sample sizes for constructing confidence intervals and testing hypotheses. Stat Med 8:803–811
Burton BR et al (2009) Size matters: just how big is BIG? Int J Epidemiol 38:263–273
Daly LE (2008) Confidence intervals and sample sizes. In: Statistics with confidence, 2nd edn. BMJ Books, London, pp 139–152. ISBN 9780727913753
Edwards BJ et al (2005) Power and sample size calculations in the presence of phenotype errors for case/control genetic association studies. BMC Genet 6:18
Goodman SN, Berlin JA (1994) The use of predicted confidence intervals when planning experiments and the misuse of power when interpreting results. Ann Intern Med 121:200–206
Greenland S (1988) On sample size and power calculations for studies using confidence intervals. Am J Epidemiol 128:231–237
Hilden J (1998) Book review of Lang TA and Secic M: ‘How to report statistics in medicine. Annotated guidelines for authors, editors and reviewers’. Med Decis Making 18:351–352
Kirkwood BR, Sterne JAC (2003) Essential medical statistics, 2nd edn. Blackwell Science, Malden, pp 1–501. ISBN 9780865428713
Meinert CL (1986) Clinical trials. Design, conduct and analysis. Oxford University Press, Oxford, pp 1–469. ISBN 0195035682
Miettinen OS (1985) Theoretical epidemiology. Delmar, New York, pp 1–359. ISBN 0827343132
Snedecor GW, Cochran WG (1980) Statistical methods, 7th edn. The Iowa State University Press, Ames, pp 1–507. ISBN 0813815606
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Brestoff, J.R., Van den Broeck, J. (2013). Study Size Planning. In: Van den Broeck, J., Brestoff, J. (eds) Epidemiology: Principles and Practical Guidelines. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5989-3_7
Download citation
DOI: https://doi.org/10.1007/978-94-007-5989-3_7
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-5988-6
Online ISBN: 978-94-007-5989-3
eBook Packages: MedicineMedicine (R0)