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Sample size calculations: basic principles and common pitfalls

Nephrology Dialysis Transplantation · 2010 · Vol. 25(5) · pp. 1388–1393
M. NoordzijGiovanni TripepiFriedo W. DekkerCarmine ZoccaliMichael W.T. TanckKitty J. Jager

Abstract

One of the most common requests that statisticians get from investigators are sample size calculations or sample size justifications. The sample size is the number of patients or other experimental units included in a study, and determining the sample size required to answer the research question is one of the first steps in designing a study. Although most statistical textbooks describe techniques for sample size calculation, it is often difficult for investigators to decide which method to use. There are many formulas available which can be applied for different types of data and study designs. However, all of these formulas should be used with caution since they are sensitive to errors, and small differences in selected parameters can lead to large differences in the sample size. In this paper, we discuss the basic principles of sample size calculations, the most common pitfalls and the reporting of these calculations.

Statistical Methods in Clinical TrialsMeta-analysis and systematic reviewsStatistical Methods and Bayesian InferenceSample size determinationSample (material)MedicineStatisticsLarge sampleComputer scienceMathematics

MeSH terms

HumansRandomized Controlled Trials as TopicSample Size
Citations
440
FWCI
2.99
field-weighted impact
References
18
Percentile
92%
vs. same field & year
Citations per year
References
An Introduction to Medical Statistics.
Journal of the American Medical Association · 1931 · 2,096 citations
Simple sample size calculation for cluster-randomized trials
International Journal of Epidemiology · 1999 · 836 citations
Practical Statistics for Medical Research.
Biometrics · 1992 · 11,721 citations
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Sample size calculations: basic principles and common pitfalls · Scinovex