A Bayesian approach to mitigation of publication bias


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.


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


    title   = {{A} {B}ayesian approach to mitigation of publication bias},
    author  = {Guan, Maime and Vandekerckhove, Joachim},
    year    = {2016},
    journal = {Psychonomic Bulletin \& Review},
    volume  = {23},
    pages   = {74--86}