Sample size calculations: basic principles and common pitfalls

Abstract
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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.

Conclusions

In conclusion, the calculation of the sample size is one of the first and most important steps in designing a study. Although techniques for sample size calculations are described in many statistical textbooks, performing these calculations can be complicated. Because sample size calculations are sensitive to errors and because of the high costs related to performing an RCT, we recommend to perform the calculations with caution or to ask for statistical advice during the designing phase of the study.

http://ndt.oxfordjournals.org/content/25/5/1388.long
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