• Steven Muncer, Shirley Taylor, and Mark Craigie.
• Department of Applied Psychology, Durham University SC, University Boulevard, Thornaby, Stockton on Tees, UK. j.j.muncer@durham.ac.uk
• J Adv Nurs. 2002 May 1;38(3):274-80.

AimsThis paper highlights the lack of consideration that is given to power in the health and social sciences, which is a continuing problem with both single study research and more importantly for meta-analysis.BackgroundThe power of a study is the probability that it will lead to a statistically significant result. By ignoring power the single study researcher makes it difficult to get negative results published and therefore affects meta-analysis through publication bias. Researchers using meta-analysis, who also ignore power, then compound the problem by including studies with low power that are more likely to show significant effects.MethodA simple means of calculating an easily understood measure of effect size from a contingency table is demonstrated in this paper. A computer programme for determining the power of a study is recommended and a method of reflecting the adequacy of the power of the studies in a meta-analysis is suggested. An example of this calculation from a meta-analytic study on intravenous magnesium, which produced inaccurate results, is provided.ConclusionIt is demonstrated that incorporating power analysis into this meta-analysis would have prevented misleading conclusions being reached. Some suggestions are made for changes in the protocol of meta-analytic studies, which highlight the importance of power analysis.

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