Conflict of interest: JJB is founder and owner of Epigear International Pty Ltd, which makes the MetaXL software.
Methods for the bias adjustment of meta-analyses of published observational studies†
Article first published online: 29 JUL 2012
© 2012 John Wiley & Sons Ltd
Journal of Evaluation in Clinical Practice
Special Issue: EBM Thematic Issue
Volume 19, Issue 4, pages 653–657, August 2013
How to Cite
Doi, S. A. R., Barendregt, J. J. and Onitilo, A. A. (2013), Methods for the bias adjustment of meta-analyses of published observational studies. Journal of Evaluation in Clinical Practice, 19: 653–657. doi: 10.1111/j.1365-2753.2012.01890.x
This article was published online on July 29, 2012. Errors in two equations in the appendix were subsequently identified. This notice is included in the online and print versions to indicate that both have been corrected [February 26, 2013].
- Issue published online: 28 JUL 2013
- Article first published online: 29 JUL 2012
- Manuscript Accepted: 19 JUN 2012
- bias adjustment;
A unique challenge in meta-analysis of observational studies is bias adjustment. Two different approaches have been proposed for doing this – using summary scores versus component scores. The prevailing view on this matter is that summary quality scores are inaccurate because information from its components can cancel each other out.
A head-to-head comparison of the component score adjustment with our method using summary scores is undertaken, using data reported by the authors of the component method.
It is demonstrated that the consideration of components or of aggregate scores does indeed lead to the same conclusions. Yet, the latter does not require imputation of the direction and magnitude of changes to effect sizes.
The summary quality score used for bias adjustment within the context of an appropriate model may be most expedient. Implications for the bias adjustment of meta-analyses of observational studies are discussed.