Sample size estimates are critical to the planning and interpretation of clinical studies, whether they are descriptive or analytical. Too small a sample size will result in imprecise estimates in a descriptive study and failure to achieve ‘statistical significance’ in an analytic or comparative study. Here we discuss what both researchers and readers should understand about the reasons for sample size estimates, how they are done and how achieving or not achieving the desired sample size can affect the interpretation of the outcomes.
- research, methods
- research, clinical
Statistics from Altmetric.com
Contributors EW conceived of the manuscript and wrote the original draft. ZHH reviewed and modified the manuscript significantly. Both authors take full responsibility for the content of the paper. The authors wish to thank the statistical experts at the School of Health and Related Research at the University of Sheffield for their helpful input to this paper.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient consent Not required.
Provenance and peer review Not commissioned; internally peer reviewed.
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.