Neglect of publication bias compromises meta-analyses of educational research

PLoS One. 2021 Jun 3;16(6):e0252415. doi: 10.1371/journal.pone.0252415. eCollection 2021.

Abstract

Because negative findings have less chance of getting published, available studies tend to be a biased sample. This leads to an inflation of effect size estimates to an unknown degree. To see how meta-analyses in education account for publication bias, we surveyed all meta-analyses published in the last five years in the Review of Educational Research and Educational Research Review. The results show that meta-analyses usually neglect publication bias adjustment. In the minority of meta-analyses adjusting for bias, mostly non-principled adjustment methods were used, and only rarely were the conclusions based on corrected estimates, rendering the adjustment inconsequential. It is argued that appropriate state-of-the-art adjustment (e.g., selection models) should be attempted by default, yet one needs to take into account the uncertainty inherent in any meta-analytic inference under bias. We conclude by providing practical recommendations on dealing with publication bias.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomedical Research*
  • Humans
  • Journalism, Medical
  • Meta-Analysis as Topic*
  • Publication Bias*

Grants and funding

This work was funded by project PRIMUS/20/HUM/009 and by the Slovak Research and Development Agency under Grant no. [APVV- 17-0418 and APVV-18-0140]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.