Combining study outcome measures using dominance adjusted weights
Article first published online: 7 JAN 2013
Copyright © 2013 John Wiley & Sons, Ltd.
Research Synthesis Methods
Volume 4, Issue 2, pages 188–197, June 2013
How to Cite
Makambi, K. H. and Lu, W. (2013), Combining study outcome measures using dominance adjusted weights. Res. Synth. Method, 4: 188–197. doi: 10.1002/jrsm.1073
- Issue published online: 19 JUN 2013
- Article first published online: 7 JAN 2013
- Manuscript Accepted: 7 DEC 2012
- Manuscript Revised: 12 OCT 2012
- Manuscript Received: 4 AUG 2011
- random effects model;
- heterogeneity variance estimator;
- mean squared error
Weighting of studies in meta-analysis is usually implemented by using the estimated inverse variances of treatment effect estimates. However, there is a possibility of one study dominating other studies in the estimation process by taking on a weight that is above some upper limit. We implement an estimator of the heterogeneity variance that takes advantage of dominance adjusted weights. The performance of this estimator is compared with that of the commonly used estimator in meta-analysis, the DerSimonian–Laird estimator. Two test procedures for the overall treatment effect are proposed that are based on the quadratic form associated with the proposed heterogeneity variance estimator. An example is given to illustrate the application of these procedures. Copyright © 2013 John Wiley & Sons, Ltd.