Evidence-based sample size estimation based upon an updated meta-regression analysis
Version of Record online: 21 SEP 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Research Synthesis Methods
Volume 3, Issue 4, pages 269–284, December 2012
How to Cite
Rotondi, M. A., Donner, A. and Koval, J. J. (2012), Evidence-based sample size estimation based upon an updated meta-regression analysis. Res. Synth. Method, 3: 269–284. doi: 10.1002/jrsm.1055
- Issue online: 10 DEC 2012
- Version of Record online: 21 SEP 2012
- Manuscript Accepted: 19 JUL 2012
- Manuscript Revised: 12 JUL 2012
- Manuscript Received: 12 APR 2011
- sample size estimation;
- evidence synthesis;
- study design;
A traditional meta-analysis examines the overall effectiveness of an intervention by producing a pooled estimate of treatment efficacy. In contrast to this, a meta-regression model seeks to determine whether a study-level covariate (X) is a plausible source of heterogeneity in a set of treatment effects.
Upon performing such an analysis, the results may suggest the presence of a meaningful amount of variation in the treatment effects because of the covariate; however, the current set of trials may not provide sufficient statistical power for such a conclusion.
The proposed approach provides quantitative insight into the amount of support that a new trial may provide to the hypothesis that X is a meaningful source of variation in an updated meta-regression model, which includes both the previously completed and the proposed trial. This empirical algorithm allows examination of the potential feasibility of a planned study of various sizes to further support or refute the hypothesis that X is a statistically significant source of variation.
A detailed example illustrates the sample size estimation algorithm for both a planned individually or cluster randomized trial to investigate the now commonly accepted impact of geographical latitude on the observed effectiveness of the Bacillus Calmette-Guérin vaccine in the prevention of tuberculosis. Copyright © 2012 John Wiley & Sons, Ltd.