Planning Study Size Based on Precision Rather Than Power

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Abstract

Study size has typically been planned based on statistical power and therefore has been heavily influenced by the philosophy of statistical hypothesis testing. A worthwhile alternative is to plan study size based on precision, for example by aiming to obtain a desired width of a confidence interval for the targeted effect. This article presents formulas for planning the size of an epidemiologic study based on the desired precision of the basic epidemiologic effect measures.

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