Four simple ways to increase power without increasing the sample size
- Published
- Accepted
- Subject Areas
- Animal Behavior, Neuroscience, Drugs and Devices, Ethical Issues, Statistics
- Keywords
- Power, Sample size, Experimental design, Statistics, Data analysis
- Copyright
- © 2017 Lazic
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2017. Four simple ways to increase power without increasing the sample size. PeerJ Preprints 5:e3363v1 https://doi.org/10.7287/peerj.preprints.3363v1
Abstract
Underpowered experiments have three problems: the probability of a false positive result is higher, true effects are harder to detect, and the true effects that are detected tend to have inflated effect sizes. Many biology experiments are underpowered and recent calls to change the traditional 0.05 significance threshold to a more stringent value of 0.005 will further reduce the power of the average experiment. Increasing power by increasing the sample size is often the only option considered, but more samples increases costs, makes the experiment harder to conduct, and is contrary to the 3Rs principles for animal research. We show how the design of an experiment and some analytical decisions can have a surprisingly large effect on power.
Author Comment
This is a preprint submission to PeerJ Preprints.
Supplemental Information
R code
R code to reproduce the figures and analyses.
