Statistics in Brief: The Importance of Sample Size in the Planning and Interpretation of Medical Research
Open accessAbstract
The increasing volume of research by the medical community often leads to increasing numbers of contradictory findings and conclusions. Although the differences observed may represent true differences, the results also may differ because of sampling variability as all studies are performed on a limited number of specimens or patients. When planning a study reporting differences among groups of patients or describing some variable in a single group, sample size should be considered because it allows the researcher to control for the risk of reporting a false-negative finding (Type II error) or to estimate the precision his or her experiment will yield. Equally important, readers of medical journals should understand sample size because such understanding is essential to interpret the relevance of a finding with regard to their own patients. At the time of planning, the investigator must establish (1) a justifiable level of statistical significance, (2) the chances of detecting a difference of given magnitude between the groups compared, ie, the power, (3) this targeted difference (ie, effect size), and (4) the variability of the data (for quantitative data). We believe correct planning of experiments is an ethical issue of concern to the entire community.
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Trials with smaller sample sizes might result in an exaggerated treatment effect.
“The sensitivity analysis indicated that bibliotherapy was not significantly more effective in trials with large samples; however, a possible explanation is that trials with smaller sample sizes might result in an exaggerated treatment effect.53”
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- Authors
- Biau, D. J., Kernéis, S., & Porcher, R.
- Affiliations
- Inserm (FR)
- Corresponding author
- Biau, David Jean
- Venue
- Clinical Orthopaedics and Related Research
- Published
- 2008-06-20
- Volume
- 466
- Issue
- 9
- Pages
- 2282-2288
- ISSN
- 0009-921X (ISSN-L)
- 1528-1132
- PMC
- PMC2493004
- OpenAlex
- W2061128187
- Cited by
- 428
- References
- 39
- Citations by year
- 2026: 35 · 2025: 62 · 2024: 32 · 2023: 34 · 2022: 43 · 2021: 50 · 2020: 54 · 2019: 25 · 2018: 23 · 2017: 18 · 2016: 13 · 2015: 8 · 2014: 5 · 2013: 8 · 2012: 3
- FWCI
- 4.72
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Clinical Orthopaedics and Related Research (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- sample size, statistical power, type II error, effect size, sampling variability, study design planning, statistical significance, research ethics
- MeSH terms
- Confidence Intervals, Odds Ratio, Sample Size, Biomedical Research
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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