Publication Bias in the Organizational Sciences

Abstract

Publication bias poses multiple threats to the accuracy of meta-analytically derived effect sizes and related statistics. Unfortunately, a review of the literature indicates that unlike meta-analytic reviews in medicine, research in the organizational sciences tends to pay little attention to this issue. In this article, the authors introduce advances in meta-analytic techniques from the medical and related sciences for a comprehensive assessment and evaluation of publication bias. The authors illustrate their use on a data set on employment interview validities. Using multiple methods, including contour-enhanced funnel plots, trim and fill, Egger’s test of the intercept, Begg and Mazumdar’s rank correlation, meta-regression, cumulative meta-analysis, and selection models, the authors find limited evidence of publication bias in the studied data.