Literature DB >> 28127782

Finding the power to reduce publication bias.

T D Stanley1, Hristos Doucouliagos2, John P A Ioannidis3.   

Abstract

The central purpose of this study is to document how a sharper focus upon statistical power may reduce the impact of selective reporting bias in meta-analyses. We introduce the weighted average of the adequately powered (WAAP) as an alternative to the conventional random-effects (RE) estimator. When the results of some of the studies have been selected to be positive and statistically significant (i.e. selective reporting), our simulations show that WAAP will have smaller bias than RE at no loss to its other statistical properties. When there is no selective reporting, the difference between RE's and WAAP's statistical properties is practically negligible. Nonetheless, when selective reporting is especially severe or heterogeneity is very large, notable bias can remain in all weighted averages. The main limitation of this approach is that the majority of meta-analyses of medical research do not contain any studies with adequate power (i.e. >80%). For such areas of medical research, it remains important to document their low power, and, as we demonstrate, an alternative unrestricted weighted least squares weighted average can be used instead of WAAP.
Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Entities:  

Keywords:  meta-analysis; publication bias; random-effects; statistical power; weighted least squares

Mesh:

Year:  2017        PMID: 28127782     DOI: 10.1002/sim.7228

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


  9 in total

1.  Sexual orientation concealment and mental health: A conceptual and meta-analytic review.

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2.  Current Status and Future Opportunities in Modeling Clinical Characteristics of Multiple Sclerosis.

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Journal:  Front Neurol       Date:  2022-05-27       Impact factor: 4.086

3.  Heterogeneity estimates in a biased world.

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Journal:  PLoS One       Date:  2022-02-03       Impact factor: 3.240

4.  Publication bias examined in meta-analyses from psychology and medicine: A meta-meta-analysis.

Authors:  Robbie C M van Aert; Jelte M Wicherts; Marcel A L M van Assen
Journal:  PLoS One       Date:  2019-04-12       Impact factor: 3.240

5.  A simple model suggesting economically rational sample-size choice drives irreproducibility.

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Journal:  PLoS One       Date:  2020-03-11       Impact factor: 3.240

6.  Using Monte Carlo experiments to select meta-analytic estimators.

Authors:  Sanghyun Hong; W Robert Reed
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7.  The prevalence of soil transmitted helminth infections in minority indigenous populations of South-East Asia and the Western Pacific Region: A systematic review and meta-analysis.

Authors:  Beth Gilmour; Kefyalew Addis Alene; Archie C A Clements
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Review 8.  Evaluating the effects of maternal positions in childbirth: An overview of Cochrane Systematic Reviews.

Authors:  Marion Kibuka; Amy Price; Igho Onakpoya; Stephanie Tierney; Mike Clarke
Journal:  Eur J Midwifery       Date:  2021-12-21

9.  Low statistical power and overestimated anthropogenic impacts, exacerbated by publication bias, dominate field studies in global change biology.

Authors:  Yefeng Yang; Helmut Hillebrand; Malgorzata Lagisz; Ian Cleasby; Shinichi Nakagawa
Journal:  Glob Chang Biol       Date:  2021-12-10       Impact factor: 13.211

  9 in total

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