Premium
Outlier and influence diagnostics for meta‐analysis
Author(s) -
Viechtbauer Wolfgang,
Cheung Mike W.L.
Publication year - 2010
Publication title -
research synthesis methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.376
H-Index - 35
eISSN - 1759-2887
pISSN - 1759-2879
DOI - 10.1002/jrsm.11
Subject(s) - outlier , meta analysis , robustness (evolution) , computer science , context (archaeology) , random effects model , econometrics , data mining , artificial intelligence , mathematics , medicine , paleontology , biochemistry , chemistry , biology , gene
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.