The importance of power and sample size estimation for study design and analysis.
- research design
- sample size
- statistics
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Footnotes
- Correction notice Following recent feedback from a reader, the authors have corrected this article. The original version of this paper stated that: “Strictly speaking, “power” refers to the number of patients required to avoid a type II error in a comparative study.” However, the formal definition of “power” is that it is the probability of avoiding a type II error (rejecting the alternative hypothesis when it is true), rather than a reference to the number of patients. Power is, however, related to sample size as power increases as the number of patients in the study increases. This statement has therefore been corrected to: “Strictly speaking, “power” refers to the probability of avoiding a type II error in a comparative study.
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