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- Published on: 8 July 2023
- Published on: 8 July 2023This article incorrectly defines "power" and should not have been published.
The following quote from the article is incorrect and misses the basic definition of power: "Strictly speaking 'power' refers to the number of patients required to avoid a type II error in a comparative study. Sample size estimation is a more encompassing term that looks at more than just the type II error and is applicable to all types of studies. In common parlance the terms are used interchangeably."
"Power" is the probability that the test correctly rejects the null hypothesis H0 when a specific alternative hypothesis H1 is true. It's equal to 1 - type II error probability. "Power" and "sample size" are not the same thing and they are not used interchangeably. It's possible to derive power given sample size, or calculate sample size based on desired power.
Please correct the article as it'll be highly misleading to beginners.
Conflict of Interest:
None declared.