Outlier and influence diagnostics for meta‐analysis

The presence of outliers and influential cases may affect the validity and robustness of the conclusions from a meta‐analysis. While researchers generally agree that it is necessary to examine outlier and influential case diagnostics when conducting a meta‐analysis, limited studies have addressed how to obtain such diagnostic measures in the context of a meta‐analysis. The present paper extends standard diagnostic procedures developed for linear regression analyses to the meta‐analytic fixed‐ and random/mixed‐effects models. Three examples are used to illustrate the usefulness of these procedures in various research settings. Issues related to these diagnostic procedures in meta‐analysis are also discussed. Copyright © 2010 John Wiley & Sons, Ltd.