Publication Bias in Meta-Analysis: Prevention, Assessment and Adjustments / Edition 1

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Overview

Publication bias is the tendency to decide to publish a study based on the results of the study, rather than on the basis of its theoretical or methodological quality. It can arise from selective publication of favorable results, or of statistically significant results. This threatens the validity of conclusions drawn from reviews of published scientific research. Meta-analysis is now used in numerous scientific disciplines, summarizing quantitative evidence from multiple studies. If the literature being synthesised has been affected by publication bias, this in turn biases the meta-analytic results, potentially producing overstated conclusions. Publication Bias in Meta-Analysis examines the different types of publication bias, and presents the methods for estimating and reducing publication bias, or eliminating it altogether. Written by leading experts, adopting a practical and multidisciplinary approach. Provides comprehensive coverage of the topic including: *Different types of publication bias, *Mechanisms that may induce them, *Empirical evidence for their existence, *Statistical methods to address them, *Ways in which they can be avoided. *Features worked examples and common data sets throughout. *Explains and compares all available software used for analysing and reducing publication bias. *Accompanied by a website featuring software, data sets and further material. Publication Bias in Meta-Analysis adopts an inter-disciplinary approach and will make an excellent reference volume for any researchers and graduate students who conduct systematic reviews or meta-analyses. University and medical libraries, as well as pharmaceutical companies and government regulatory agencies, will also find this invaluable.

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Editorial Reviews

From the Publisher
“The book adopts an inter-disciplinary approach and willmake a useful reference volume for any researchers and graduatestudents who conduct systematic reviews or meta-analyses.University and medical libraries, as well as pharmaceuticalcompanies and government regulatory agencies, will also find thisinvaluable.”  (Zentralblatt MATH, 2012)

"…a well-written book and will be useful for researchers orgraduate students…" (Journal of the American StatisticalAssociation, June 2007)

"...the book definatly succeeds in raising the awareness of thereader to an issue that unfortunately still remainsunderappreciated" (Psychometrika June 2007)

" … an incredibly thorough, useful book. The impressivelist of contributors … is the book’s particularstrength." (JRSSA, Vol. 169, No. 4, October 2006)

"…a useful introduction to meta-analysisand…state-of-the-art description of the statistical problemsassociated…of particular value as a reference for amulti-disciplinary audience…" (Biometrics, June2006)

"This book will have a wide appeal and is a major contributionto ways of distilling evidence from scientific literature."(Journal of Tropical Pediatrics, June 2006)

“I predict that this book will become the key text in thearea.”  (Short Book Reviews, April 2006)

"…likely to become a standard reference for those whocarry systematic literature reviews." (Psychometrika, June2007)

"This elegant hardcover book brings together 16 finecontributions and three appendices...It is obviously a must formedical libraries."  (Journal of Applied Science,2007)

"A strong and rigorous collection of timely essays that will beuseful for advanced scholars and experienced researchers in variousdisciplines…. It is an obvious must for medical libraries."(Journal of Applied Statistics, December 2007)

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Product Details

  • ISBN-13: 9780470870143
  • Publisher: Wiley
  • Publication date: 12/5/2005
  • Edition number: 1
  • Pages: 376
  • Product dimensions: 6.26 (w) x 9.29 (h) x 1.04 (d)

Meet the Author

Hannah Rothstein is co-chair of the Methods Group of theCampbell Collaboration, and a member of the Collaboration’sSteering Group. She is also a member of the CochraneCollaboration’s reporting bias methods group. Dr. Rothsteinhas been first author of four published meta-analyses of employmentselection methods and has written many articles on methodologicalissues in meta-analysis. She has authored a chapter onmeta-analysis that appeared in Measuring and Analyzing Behaviorin Organizations, and has completed a 25-year retrospective onthe contributions of meta-analysis to the field of industrial andorganizational psychology that appeared in ValidityGeneralization: A Critical Review. With Michael Borenstein, andothers, she is the author of computer software for meta-analysisand power analysis.

Alex Sutton has published extensively on meta-analysismethodology generally, and on publication bias specifically inrecent years, including a major systematic review on the topic ofthe methodology that has been developed for meta-analysis. Hecurrently has an active interest in the area of partially reportedstudy information, which is currently under-researched. Dr. Suttonis co-author of a textbook on metaanalysis (Methods for MetaAnalysis in Medical Research), which was published by Wiley in2000.

Michael Borenstein served as Director of Biostatistics atHillside Hospital, Long Island Jewish Medical Center from1980–2002, and as Associate Professor at Albert EinsteinCollege of Medicine from 1992–2002. He has served on variousreview groups and advisory panels for the National Institutes ofHealth and as a member of the NIMH Data Safety Monitoring Board,and is an active member of the statistical advisory groups of theCochrane and Campbell Collaborations. Since the mid-1990s, DrBorenstein has lectured widely on meta-analysis. He is the PI onseveral NIH grants to develop software for meta-analysis and is thedeveloper, with Larry Hedges, Julian Higgins, Hannah Rothstein andothers, of Comprehensive Meta Analysis, a best-sellingcomputer program for meta-analysis.

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Table of Contents

Preface.

Acknowledgements.

Notes on Contributors.

Chapter 1: Publication Bias in Meta-Analysis (Hannah R.Rothstein, Alexander J. Sutton and Michael Borenstein).

Part A: Publication bias in context.

Chapter 2: Publication Bias: Recognizing the Problem,Understanding Its Origins and Scope, and Preventing Harm (KayDickersin).

Chapter 3: Preventing Publication Bias: Registries andProspective Meta-Analysis (Jesse A. Berlin and Davina Ghersi).

Chapter 4: Grey Literature and Systematic Reviews (SallyHopewell, Mike Clarke and Sue Mallett).

Part B: Statistical methods for assessing publicationbias.

Chapter 5: The Funnel Plot (Jonathan A.C. Sterne, Betsy JaneBecker and Matthias Egger).

Chapter 6: Regression Methods to Detect Publication and OtherBias in Meta-Analysis (Jonathan A.C. Sterne and MatthiasEgger).

Chapter 7: Failsafe N or File-Drawer Number (Betsy JaneBecker).

Chapter 8: The Trim and Fill Method (Sue Duval).

Chapter 9: Selection Method Approaches (Larry V. Hedges and JackVevea).

Chapter 10: Evidence Concerning the Consequences of Publicationand Related Biases (Alexander J. Sutton).

Chapter 11: Software for Publication Bias (MichaelBorenstein).

Part C: Advanced and emerging approaches.

Chapter 12: Bias in Meta-Analysis Induced by IncompletelyReported Studies (Alexander J. Sutton and Therese D. Pigott).

Chapter 13: Assessing the Evolution of Effect Sizes over Time(Thomas A. Trikalinos and John P.A. Ioannidis).

Chapter 14: Do Systematic Reviews Based on Individual PatientData Offer a Means of Circumventing Biases Associated with TrialPublications? (Lesley Stewart, Jayne Tierney and SarahBurdett).

Chapter 15: Differentiating Biases from Genuine Heterogeneity:Distinguishing Artifactual from Substantive Effects (John P.A.Ioannidis).

Chapter 16: Beyond Conventional Publication Bias: OtherDeterminants of Data Suppression (Scott D. Halpern and Jesse A.Berlin).

Appendices.

Appendix A: Data Sets.

Appendix B: Annotated Bibliography (Hannah R. Rothstein andAshley Busing).

Glossary.

Index.

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