A Bayesian approach to mitigation of publication bias

M. Guan and J. Vandekerckhove The reliability of published research findings in psychology has been a topic of rising concern. Publication bias, or treating positive findings differently from negative findings, is a contributing factor to this "crisis of confidence," in that it likely inflates the number of false-positive effects in the literature. We demonstrate a Bayesian model averaging approach that takes into account the possibility of publication bias and allows for a better estimate of true underlying effect size. Accounting for the possibility of bias leads to a more conservative interpretation of published studies as well as meta-analyses. We provide mathematical details of the method and examples. DOI: 10.3758/s13423-015-0868-6


Guan, M., & Vandekerckhove, J. (2016). A Bayesian approach to mitigation of publication bias. Psychonomic Bulletin & Review, 23, 74–86.


  title     = {A Bayesian approach to mitigation of publication bias},
  author    = {Guan, M. and Vandekerckhove, J.},
  journal   = {Psychonomic Bulletin \& Review},
  year      = {2016},
  volume    = {23},
  pages     = {74--86},
  doi       = {10.3758/s13423-015-0868-6},