This article provides an introduction to power analysis so that readers have a basis for understanding the importance of statistical power when planning research and interpreting the results. A simple hypothetical study is used as the context for discussion. The concepts of false findings and missed findings are introduced as a way of thinking about type I and type II errors. The primary factors that affect power are described and examples are provided. Finally, examples are presented to demonstrate 2 uses of power analysis, 1 for prospectively estimating the sample size needed to insure finding effects of a known magnitude in a study and 1 for retrospectively estimating power to gauge the likelihood that an effect was missed.
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Norton et al. (2001) studied this question.
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