title: Outlier and influence diagnostics for meta-analysis.
abstract: 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.
authors.affiliation: Department of Methodology and Statistics, Maastricht University, Maastricht, The Netherlands. wolfgang.viechtbauer@stat.unimaas.nl.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Viechtbauer
authors.affiliation: Department of Psychology, National University of Singapore, Singapore, Singapore.
authors.forename: Mike W-L
authors.initials: MW
authors.lastname: Cheung
keywords: influence diagnostics; meta‐analysis; mixed‐effects model; outliers