Outlier and influence diagnostics for meta-analysis
Outlier and influence diagnostics for meta-analysis
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DOI：
10.1002/jrsm.11
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发表时间：
2010-04-01
影响因子：
9.8
通讯作者：
Cheung, Mike W. -L.
中科院分区：
文献类型：
--
作者：
Viechtbauer, Wolfgang;Cheung, Mike W. -L.
异常值和有影响力的案例的存在可能会影响荟萃分析结论的有效性和稳健性。虽然研究人员普遍认为，在进行荟萃分析时有必要检查离群点和有影响力的病例诊断，但在荟萃分析的背景下，如何获得此类诊断措施的研究有限。本文将为线性回归分析开发的标准诊断程序扩展到元分析、固定和随机/混合效应模型。三个例子被用来说明这些程序在各种研究环境中的有用性。文中还讨论了Meta分析中与这些诊断程序有关的问题。版权所有(C)2010 John Wiley&Sons，Ltd.
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 (C) 2010 John Wiley & Sons, Ltd.