Literature DB >> 17397112

A simple method for inference on an overall effect in meta-analysis.

Sarah E Brockwell1, Ian R Gordon.   

Abstract

The random effects approach in meta-analysis due to DerSimonian and Laird is well established and used pervasively. It has been established by Brockwell and Gordon that this method, when used for confidence intervals, leads to coverage probabilities lower than the nominal value. A number of alternatives have been proposed, but these either have the defect of iterative and complicated calculation, or deficient coverage. In this paper we propose a new approach, which is simple to use, and has coverage probabilities better than the alternatives, based on extensive simulation. We call this approach the 'quantile approximation' method. Copyright 2007 John Wiley & Sons, Ltd.

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Year:  2007        PMID: 17397112     DOI: 10.1002/sim.2883

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  11 in total

1.  NONPARAMETRIC INFERENCE PROCEDURE FOR PERCENTILES OF THE RANDOM EFFECTS DISTRIBUTION IN META-ANALYSIS.

Authors:  Rui Wang; Lu Tian; Tianxi Cai; L J Wei
Journal:  Ann Appl Stat       Date:  2010       Impact factor: 2.083

2.  Extending DerSimonian and Laird's methodology to perform network meta-analyses with random inconsistency effects.

Authors:  Dan Jackson; Martin Law; Jessica K Barrett; Rebecca Turner; Julian P T Higgins; Georgia Salanti; Ian R White
Journal:  Stat Med       Date:  2015-09-30       Impact factor: 2.373

3.  A comparison of seven random-effects models for meta-analyses that estimate the summary odds ratio.

Authors:  Dan Jackson; Martin Law; Theo Stijnen; Wolfgang Viechtbauer; Ian R White
Journal:  Stat Med       Date:  2018-01-08       Impact factor: 2.373

4.  Clinical, laboratory and radiological characteristics and outcomes of novel coronavirus (SARS-CoV-2) infection in humans: A systematic review and series of meta-analyses.

Authors:  Israel Júnior Borges do Nascimento; Thilo Caspar von Groote; Dónal P O'Mathúna; Hebatullah Mohamed Abdulazeem; Catherine Henderson; Umesh Jayarajah; Ishanka Weerasekara; Tina Poklepovic Pericic; Henning Edgar Gerald Klapproth; Livia Puljak; Nensi Cacic; Irena Zakarija-Grkovic; Silvana Mangeon Meirelles Guimarães; Alvaro Nagib Atallah; Nicola Luigi Bragazzi; Milena Soriano Marcolino; Ana Marusic; Ana Jeroncic
Journal:  PLoS One       Date:  2020-09-17       Impact factor: 3.240

5.  Road Traffic Noise Exposure and Birth Outcomes: An Updated Systematic Review and Meta-Analysis.

Authors:  Angel M Dzhambov; Peter Lercher
Journal:  Int J Environ Res Public Health       Date:  2019-07-15       Impact factor: 3.390

6.  A re-evaluation of the 'quantile approximation method' for random effects meta-analysis.

Authors:  Dan Jackson; Jack Bowden
Journal:  Stat Med       Date:  2009-01-30       Impact factor: 2.373

7.  The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method.

Authors:  Joanna IntHout; John P A Ioannidis; George F Borm
Journal:  BMC Med Res Methodol       Date:  2014-02-18       Impact factor: 4.615

8.  Approximate confidence intervals for moment-based estimators of the between-study variance in random effects meta-analysis.

Authors:  Dan Jackson; Jack Bowden; Rose Baker
Journal:  Res Synth Methods       Date:  2015-08-19       Impact factor: 5.273

9.  Empirical evidence about inconsistency among studies in a pair-wise meta-analysis.

Authors:  Kirsty M Rhodes; Rebecca M Turner; Julian P T Higgins
Journal:  Res Synth Methods       Date:  2015-12-17       Impact factor: 5.273

10.  Road Traffic Noise Exposure and Depression/Anxiety: An Updated Systematic Review and Meta-Analysis.

Authors:  Angel M Dzhambov; Peter Lercher
Journal:  Int J Environ Res Public Health       Date:  2019-10-27       Impact factor: 3.390

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