IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0215052.html
   My bibliography  Save this article

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

Author

Listed:
  • Robbie C M van Aert
  • Jelte M Wicherts
  • Marcel A L M van Assen

Abstract

Publication bias is a substantial problem for the credibility of research in general and of meta-analyses in particular, as it yields overestimated effects and may suggest the existence of non-existing effects. Although there is consensus that publication bias exists, how strongly it affects different scientific literatures is currently less well-known. We examined evidence of publication bias in a large-scale data set of primary studies that were included in 83 meta-analyses published in Psychological Bulletin (representing meta-analyses from psychology) and 499 systematic reviews from the Cochrane Database of Systematic Reviews (CDSR; representing meta-analyses from medicine). Publication bias was assessed on all homogeneous subsets (3.8% of all subsets of meta-analyses published in Psychological Bulletin) of primary studies included in meta-analyses, because publication bias methods do not have good statistical properties if the true effect size is heterogeneous. Publication bias tests did not reveal evidence for bias in the homogeneous subsets. Overestimation was minimal but statistically significant, providing evidence of publication bias that appeared to be similar in both fields. However, a Monte-Carlo simulation study revealed that the creation of homogeneous subsets resulted in challenging conditions for publication bias methods since the number of effect sizes in a subset was rather small (median number of effect sizes equaled 6). Our findings are in line with, in its most extreme case, publication bias ranging from no bias until only 5% statistically nonsignificant effect sizes being published. These and other findings, in combination with the small percentages of statistically significant primary effect sizes (28.9% and 18.9% for subsets published in Psychological Bulletin and CDSR), led to the conclusion that evidence for publication bias in the studied homogeneous subsets is weak, but suggestive of mild publication bias in both psychology and medicine.

Suggested Citation

  • Robbie C M van Aert & Jelte M Wicherts & Marcel A L M van Assen, 2019. "Publication bias examined in meta-analyses from psychology and medicine: A meta-meta-analysis," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-32, April.
  • Handle: RePEc:plo:pone00:0215052
    DOI: 10.1371/journal.pone.0215052
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0215052
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0215052&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0215052?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jack Vevea & Larry Hedges, 1995. "A general linear model for estimating effect size in the presence of publication bias," Psychometrika, Springer;The Psychometric Society, vol. 60(3), pages 419-435, September.
    2. Abel Brodeur & Mathias Lé & Marc Sangnier & Yanos Zylberberg, 2016. "Star Wars: The Empirics Strike Back," American Economic Journal: Applied Economics, American Economic Association, vol. 8(1), pages 1-32, January.
    3. Stanley, T. D. & Jarrell, Stephen B. & Doucouliagos, Hristos, 2010. "Could It Be Better to Discard 90% of the Data? A Statistical Paradox," The American Statistician, American Statistical Association, vol. 64(1), pages 70-77.
    4. Nazila Alinaghi & W. Robert Reed, 2016. "Meta-Analysis and Publication Bias: How Well Does the FAT-PET-PEESE Procedure Work?," Working Papers in Economics 16/26, University of Canterbury, Department of Economics and Finance.
    5. Sue Duval & Richard Tweedie, 2000. "Trim and Fill: A Simple Funnel-Plot–Based Method of Testing and Adjusting for Publication Bias in Meta-Analysis," Biometrics, The International Biometric Society, vol. 56(2), pages 455-463, June.
    6. Kerry Dwan & Douglas G Altman & Juan A Arnaiz & Jill Bloom & An-Wen Chan & Eugenia Cronin & Evelyne Decullier & Philippa J Easterbrook & Erik Von Elm & Carrol Gamble & Davina Ghersi & John P A Ioannid, 2008. "Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias," PLOS ONE, Public Library of Science, vol. 3(8), pages 1-31, August.
    7. Megan L Head & Luke Holman & Rob Lanfear & Andrew T Kahn & Michael D Jennions, 2015. "The Extent and Consequences of P-Hacking in Science," PLOS Biology, Public Library of Science, vol. 13(3), pages 1-15, March.
    8. Reed, W. Robert, 2015. "A Monte Carlo analysis of alternative meta-analysis estimators in the presence of publication bias," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 9, pages 1-40.
    9. J. Copas, 1999. "What works?: selectivity models and meta‐analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(1), pages 95-109.
    10. Viechtbauer, Wolfgang, 2010. "Conducting Meta-Analyses in R with the metafor Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i03).
    11. Michał Krawczyk, 2015. "The Search for Significance: A Few Peculiarities in the Distribution of P Values in Experimental Psychology Literature," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-19, June.
    12. Daniele Fanelli, 2012. "Negative results are disappearing from most disciplines and countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 891-904, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guillaume Coqueret, 2023. "Forking paths in financial economics," Papers 2401.08606, arXiv.org.
    2. Augusteijn, Hilde Elisabeth Maria & van Aert, Robbie Cornelis Maria & van Assen, Marcel A. L. M., 2021. "Posterior Probabilities of Effect Sizes and Heterogeneity in Meta-Analysis: An Intuitive Approach of Dealing with Publication Bias," OSF Preprints avkgj, Center for Open Science.
    3. Henkel, Malin & Boffelli, Albachiara & Olhager, Jan & Kalchschmidt, Matteo, 2022. "A case survey of offshoring–backshoring cases: The influence of contingency factors," International Journal of Production Economics, Elsevier, vol. 253(C).
    4. Tian, Dan & Hu, Xiao & Qian, Yuchen & Li, Jiang, 2024. "Exploring the scientific impact of negative results," Journal of Informetrics, Elsevier, vol. 18(1).
    5. Nguyen-Anh, Tuan & Hoang-Duc, Chinh & Tiet, Tuyen & Nguyen-Van, Phu & To-The, Nguyen, 2022. "Composite effects of human, natural and social capitals on sustainable food-crop farming in Sub-Saharan Africa," Food Policy, Elsevier, vol. 113(C).
    6. Mangirdas Morkunas & Elzė Rudienė & Lukas Giriūnas & Laura Daučiūnienė, 2020. "Assessment of Factors Causing Bias in Marketing- Related Publications," Publications, MDPI, vol. 8(4), pages 1-16, October.
    7. Kim, Bitna, 2022. "Publication bias: A “bird's-eye view” of meta-analytic practice in criminology and criminal justice," Journal of Criminal Justice, Elsevier, vol. 78(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sanghyun Hong & W. Robert Reed, 2020. "Using Monte Carlo Experiments to Select Meta-Analytic Estimators," Working Papers in Economics 20/10, University of Canterbury, Department of Economics and Finance.
    2. van Aert, Robbie Cornelis Maria & van Assen, Marcel A. L. M., 2018. "P-uniform," MetaArXiv zqjr9, Center for Open Science.
    3. Furukawa, Chishio, 2019. "Publication Bias under Aggregation Frictions: Theory, Evidence, and a New Correction Method," EconStor Preprints 194798, ZBW - Leibniz Information Centre for Economics.
    4. Irsova, Zuzana & Bom, Pedro Ricardo Duarte & Havranek, Tomas & Rachinger, Heiko, 2023. "Spurious Precision in Meta-Analysis," MetaArXiv 3qp2w, Center for Open Science.
    5. van Aert, Robbie Cornelis Maria, 2018. "Dissertation R.C.M. van Aert," MetaArXiv eqhjd, Center for Open Science.
    6. Sebastian Gechert & Tomas Havranek & Zuzana Irsova & Dominika Kolcunova, 2022. "Measuring Capital-Labor Substitution: The Importance of Method Choices and Publication Bias," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 45, pages 55-82, July.
    7. Augusteijn, Hilde Elisabeth Maria & van Aert, Robbie Cornelis Maria & van Assen, Marcel A. L. M., 2021. "Posterior Probabilities of Effect Sizes and Heterogeneity in Meta-Analysis: An Intuitive Approach of Dealing with Publication Bias," OSF Preprints avkgj, Center for Open Science.
    8. Nelson, Jon Paul, 2020. "Fixed-effect versus random-effects meta-analysis in economics: A study of pass-through rates for alcohol beverage excise taxes," Economics Discussion Papers 2020-1, Kiel Institute for the World Economy (IfW Kiel).
    9. Irsova, Zuzana & Doucouliagos, Hristos & Havranek, Tomas & Stanley, T. D., 2023. "Meta-Analysis of Social Science Research: A Practitioner’s Guide," EconStor Preprints 273719, ZBW - Leibniz Information Centre for Economics.
    10. Wimmer, Thomas & Geyer-Klingeberg, Jerome & Hütter, Marie & Schmid, Florian & Rathgeber, Andreas, 2021. "The impact of speculation on commodity prices: A Meta-Granger analysis," Journal of Commodity Markets, Elsevier, vol. 22(C).
    11. Sanghyun Hong & W. Robert Reed, 2019. "A Performance Analysis of Some New Meta-Analysis Estimators Designed to Correct Publication Bias," Working Papers in Economics 19/04, University of Canterbury, Department of Economics and Finance.
    12. Di Pietro Giorgio & European Commission & IZA, 2022. "Studying abroad and earnings: A meta‐analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1096-1129, September.
    13. Sanghyun Hong & W. Robert Reed, 2019. "Towards an Experimental Framework for Assessing Meta-Analysis Methods, with a Focus on Andrews-Kasy Estimators," Working Papers in Economics 19/13, University of Canterbury, Department of Economics and Finance.
    14. Bart Verkuil & Serpil Atasayi & Marc L Molendijk, 2015. "Workplace Bullying and Mental Health: A Meta-Analysis on Cross-Sectional and Longitudinal Data," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-16, August.
    15. Jindrich Matousek & Tomas Havranek & Zuzana Irsova, 2022. "Individual discount rates: a meta-analysis of experimental evidence," Experimental Economics, Springer;Economic Science Association, vol. 25(1), pages 318-358, February.
    16. Paldam, Martin, 2015. "Meta-analysis in a nutshell: Techniques and general findings," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 9, pages 1-14.
    17. Christopher Snyder & Ran Zhuo, 2018. "Sniff Tests as a Screen in the Publication Process: Throwing out the Wheat with the Chaff," NBER Working Papers 25058, National Bureau of Economic Research, Inc.
    18. Abel Brodeur, Nikolai M. Cook, Anthony Heyes, 2022. "We Need to Talk about Mechanical Turk: What 22,989 Hypothesis Tests Tell Us about Publication Bias and p-Hacking in Online Experiments," LCERPA Working Papers am0133, Laurier Centre for Economic Research and Policy Analysis.
    19. Georgiou, George K. & Guo, Kan & Naveenkumar, Nithya & Vieira, Ana Paula Alves & Das, J.P., 2020. "PASS theory of intelligence and academic achievement: A meta-analytic review," Intelligence, Elsevier, vol. 79(C).
    20. Jasper Brinkerink, 2023. "When Shooting for the Stars Becomes Aiming for Asterisks: P-Hacking in Family Business Research," Entrepreneurship Theory and Practice, , vol. 47(2), pages 304-343, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0215052. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.