Literature DB >> 16345059

The implications of publication bias for meta-analysis' other parameter.

Dan Jackson1.   

Abstract

Perhaps the greatest threat to the validity of a meta-analysis is the possibility of publication bias, where studies that are interesting or statistically significant are more likely to be published than those with less encouraging results. In particular, there is the concern that this bias might be 'one-sided', where studies indicating that the treatment is beneficial have a greater probability of publication. The impact that this type of bias has on the estimate of treatment effect has received a great deal of attention but this also has implications for estimates of between-study variance. Using step functions to model the bias it can be demonstrated that it is impossible to make generalizations concerning how we should revise estimates of between-study variance when presented with the possibility of publication bias. To determine this, assumptions must be made concerning the form that the bias takes, which is unknown in practice. Copyright 2005 John Wiley & Sons, Ltd.

Mesh:

Year:  2006        PMID: 16345059     DOI: 10.1002/sim.2293

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


  16 in total

Review 1.  Heterogeneity of systematic reviews in oncology.

Authors:  Jonathan Holmes; David Herrmann; Chelsea Koller; Sarah Khan; Blake Umberham; Jody A Worley; Matt Vassar
Journal:  Proc (Bayl Univ Med Cent)       Date:  2017-04

2.  A fully Bayesian application of the Copas selection model for publication bias extended to network meta-analysis.

Authors:  Dimitris Mavridis; Alex Sutton; Andrea Cipriani; Georgia Salanti
Journal:  Stat Med       Date:  2012-07-17       Impact factor: 2.373

3.  Rejoinder to "quantifying publication bias in meta-analysis".

Authors:  Lifeng Lin; Haitao Chu
Journal:  Biometrics       Date:  2017-11-15       Impact factor: 2.571

4.  The magnitude of small-study effects in the Cochrane Database of Systematic Reviews: an empirical study of nearly 30 000 meta-analyses.

Authors:  Lifeng Lin; Linyu Shi; Haitao Chu; Mohammad Hassan Murad
Journal:  BMJ Evid Based Med       Date:  2019-07-04

5.  Heterogeneity estimates in a biased world.

Authors:  Johannes Hönekopp; Audrey Helen Linden
Journal:  PLoS One       Date:  2022-02-03       Impact factor: 3.240

6.  Bias caused by sampling error in meta-analysis with small sample sizes.

Authors:  Lifeng Lin
Journal:  PLoS One       Date:  2018-09-13       Impact factor: 3.240

7.  Assessment of regression-based methods to adjust for publication bias through a comprehensive simulation study.

Authors:  Santiago G Moreno; Alex J Sutton; A E Ades; Tom D Stanley; Keith R Abrams; Jaime L Peters; Nicola J Cooper
Journal:  BMC Med Res Methodol       Date:  2009-01-12       Impact factor: 4.615

8.  Evolution of heterogeneity (I2) estimates and their 95% confidence intervals in large meta-analyses.

Authors:  Kristian Thorlund; Georgina Imberger; Bradley C Johnston; Michael Walsh; Tahany Awad; Lehana Thabane; Christian Gluud; P J Devereaux; Jørn Wetterslev
Journal:  PLoS One       Date:  2012-07-25       Impact factor: 3.240

9.  Modelling heterogeneity variances in multiple treatment comparison meta-analysis--are informative priors the better solution?

Authors:  Kristian Thorlund; Lehana Thabane; Edward J Mills
Journal:  BMC Med Res Methodol       Date:  2013-01-11       Impact factor: 4.615

10.  Bias towards publishing positive results in orthopedic and general surgery: a patient safety issue?

Authors:  Erik A Hasenboehler; Imran K Choudhry; Justin T Newman; Wade R Smith; Bruce H Ziran; Philip F Stahel
Journal:  Patient Saf Surg       Date:  2007-11-27
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