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

• Published in: PloS one Vol. 14; no. 4; p. e0215052
• Main Authors: van Aert, Robbie C. M., Wicherts, Jelte M., van Assen, Marcel A. L. M.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 12.04.2019; Public Library of Science (PLoS)
• Subjects: Analysis; Bias; Biology and Life Sciences; Computer simulation; Data Interpretation, Statistical; Data Management; Databases, Factual; Humans; Literature reviews; Medical research; Medicine; Medicine and Health Sciences; Meta-analysis; Monte Carlo Method; Monte Carlo methods; Monte Carlo simulation; Physical Sciences; Psychological research; Psychology; Publication Bias; Quality Control; Research and Analysis Methods; Reviews; Science literature; Science Policy; Selection Bias; Social Sciences; Statistical analysis; Statistical significance; Statistics; Studies; United States > US; Netherlands
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0215052

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.