A quick primer on power

March 19, 2015
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(This article was first published on R – christopher lortie, and kindly contributed to R-bloggers)

Cohen is power. Inferential statistics primarily invoke the following four key concepts: sample size, significance criterion, effect size, and statistical power. Cohen elegantly developed the maths, benchmarks, and key semantics associated with statistical power.

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Statistical power is the long-term probability of rejecting the null hypothesis (typically assumed to be no difference between treatments) as defined by Cohen 1992. In a brief exploration of power for pilot experiments with limited numbers of available subjects, here are several current resources to facilitate the exploration of appropriate sample sizes.

Resources

pwr package in r

Binary outcome trials calculator

Fischer Exact test calculator 

Sample size calculator

Power & sample size calculator

Download G*Power app

Description of statistical power

A delightful post on power

A slide deck on design decisions/solutions for little data/pilot trials

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