Power and sample size.

Department of Biostatistical Sciences, Wake Forest University Health Sciences, Winston-Salem, NC, USA.
Methods in molecular biology (Clifton, N.J.) (Impact Factor: 1.29). 02/2007; 404:377-408. DOI: 10.1007/978-1-59745-530-5_19
Source: PubMed

ABSTRACT In this chapter, we discuss the concept of statistical power and show how the sample size can be chosen to ensure a desired power. Power is the probability of rejecting the null hypothesis when the null hypothesis is false, that is the probability of saying there is a difference when a difference actually exists. An underpowered study does not have a sufficiently large sample size to answer the research question of interest. An overpowered study has too large a sample size and wastes resources. We will show how the power and required sample size can be calculated for several common types of studies, mention software that can be used for the necessary calculations, and discuss additional considerations.

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