RESEARCH ARTICLE


Power and Error: Increased Risk of False Positive Results in Underpowered Studies



R. M. Christley*
Epidemiology and Public Health, School of Veterinary Science, Faculty of Health and Life Science, University of Liverpool, Leahurst Campus, Neston, CH64 7TE, UK


© 2010Christley et al..

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Epidemiology and Public Health, School of Veterinary Science, Faculty of Health and Life Science, University of Liverpool, Leahurst Campus, Neston, CH64 7TE, UK;Te: +44 (0) 151 794 6170; E-mail: robc@liverpool.ac.uk


Abstract

It is well recognised that low statistical power increases the probability of type II error, that is it reduces the probability of detecting a difference between groups, where a difference exists. Paradoxically, low statistical power also increases the likelihood that a statistically significant finding is actually falsely positive (for a given p-value). Hence, ethical concerns regarding studies with low statistical power should include the increased risk of type I error in such studies reporting statistically significant effects. This paper illustrates the effect of low statistical power by comparing hypothesis testing with diagnostic test evaluation using concepts familiar to clinicians, such as positive and negative predicative values. We also note that, where there is a high probability that the null hypothesis is true, statistically significant findings are even more likely to be falsely positive.