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Sample size calculations: basic principles and common pitfalls
Author(s) -
M. Noordzij,
Giovanni Tripepi,
Friedo W. Dekker,
Carmine Zoccali,
Michael W.T. Tanck,
Kitty J. Jager
Publication year - 2010
Publication title -
nephrology dialysis transplantation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.654
H-Index - 168
eISSN - 1460-2385
pISSN - 0931-0509
DOI - 10.1093/ndt/gfp732
Subject(s) - sample size determination , sample (material) , medicine , statistics , large sample , computer science , mathematics , chromatography , chemistry
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.

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