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Statistical methods for dealing with publication bias in meta‐analysis
Author(s) -
Jin ZhiChao,
Zhou XiaoHua,
He Jia
Publication year - 2014
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.6342
Subject(s) - publication bias , computer science , meta analysis , statistical analysis , data science , econometrics , statistics , medicine , mathematics
Publication bias is an inevitable problem in the systematic review and meta‐analysis. It is also one of the main threats to the validity of meta‐analysis. Although several statistical methods have been developed to detect and adjust for the publication bias since the beginning of 1980s, some of them are not well known and are not being used properly in both the statistical and clinical literature. In this paper, we provided a critical and extensive discussion on the methods for dealing with publication bias, including statistical principles, implementation, and software, as well as the advantages and limitations of these methods. We illustrated a practical application of these methods in a meta‐analysis of continuous support for women during childbirth. Copyright © 2014 John Wiley & Sons, Ltd.