Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials
Jonathan A C SterneSchool of Social and Community Medicine, University of Bristol, Bristol BS8 2PS, UK. [email protected]Alex J. SuttonUniversity of LeicesterJohn P. A. IoannidisStanford UniversityNorma TerrinInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA;David R. JonesJ. LauTufts UniversityJames R. CarpenterLondon School of Hygiene & Tropical MedicineGerta RückerUniv. of FreiburgRoger HarbordInstitute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Germany;Christopher H. SchmidTufts UniversityJennifer TetzlaffClinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada;Jonathan J DeeksUniversity of Birmingham.*Judith PetersPeninsula Medical School, University of Exeter, Exeter, UK;Petra MacaskillUniversity of SydneyGuido SchwarzerUniv. of FreiburgSue DuvalUniversity of Minnesota School of Public Health, Minneapolis, MN, USA;Douglas G. AltmanUniversity of OxfordDavid MoherOttawa Hospital Research InstituteJulian P. T. HigginsMRC Biostatistics Unit, Cambridge, UK
2011en
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Funnel plots, and tests for funnel plot asymmetry, have been widely used to examine bias in the results of meta-analyses. Funnel plot asymmetry should not be equated with publication bias, because it has a number of other possible causes. This article describes how to interpret funnel plot asymmetry, recommends appropriate tests, and explains the implications for choice of meta-analysis model
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