Abstract
Power calculations are a key study design step in research studies. However, such power analysis is often inappropriately performed in the medical literature by attempting to help interpret the findings of a completed study, instead of attempting to aid in choosing an optimal sample size for a future study. The aim of this article is to provide a brief discussion of the drawbacks of performing these post hoc power calculations, and to correspondingly suggest best practices regarding the use of statistical power and the interpretation of study results. Specifically, power analysis should always be considered before any research study in order to choose an ideal sample size and/or to examine the feasibility of properly evaluating study aims, but it should never be used in order to help interpret the results of an already completed study. Alternatively, 95% confidence intervals for effect sizes (eg, odds ratio, hazard ratio, mean difference) or other relevant parameter estimates should be used when attempting to draw conclusions from results, such as the likelihood of a type II error (ie, a false negative finding).
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