Estimating the evidential value of significant results in psychological science

PLoS One. 2017 Aug 18;12(8):e0182651. doi: 10.1371/journal.pone.0182651. eCollection 2017.

Abstract

Quantifying evidence is an inherent aim of empirical science, yet the customary statistical methods in psychology do not communicate the degree to which the collected data serve as evidence for the tested hypothesis. In order to estimate the distribution of the strength of evidence that individual significant results offer in psychology, we calculated Bayes factors (BF) for 287,424 findings of 35,515 articles published in 293 psychological journals between 1985 and 2016. Overall, 55% of all analyzed results were found to provide BF > 10 (often labeled as strong evidence) for the alternative hypothesis, while more than half of the remaining results do not pass the level of BF = 3 (labeled as anecdotal evidence). The results estimate that at least 82% of all published psychological articles contain one or more significant results that do not provide BF > 10 for the hypothesis. We conclude that due to the threshold of acceptance having been set too low for psychological findings, a substantial proportion of the published results have weak evidential support.

MeSH terms

  • Bayes Theorem
  • Humans
  • Psychology*
  • Publishing*

Grants and funding

The authors received no specific funding for this work.