Conservative tests under satisficing models of publication bias

Justin McCrary, Garret Christensen, Daniele Fanelli

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Publication bias leads consumers of research to observe a selected sample of statistical estimates calculated by producers of research. We calculate critical values for statistical significance that could help to adjust after the fact for the distortions created by this selection effect, assuming that the only source of publication bias is file drawer bias. These adjusted critical values are easy to calculate and differ from unadjusted critical values by approximately 50%-rather than rejecting a null hypothesis when the t-ratio exceeds 2, the analysis suggests rejecting a null hypothesis when the t-ratio exceeds 3. Samples of published social science research indicate that on average, across research fields, approximately 30% of published t-statistics fall between the standard and adjusted cutoffs.

Original languageEnglish
Article numbere0149590
JournalPLoS ONE
Volume11
Issue number2
DOIs
Publication statusPublished - 22 Feb 2016

ASJC Scopus subject areas

  • General Biochemistry,Genetics and Molecular Biology
  • General Agricultural and Biological Sciences
  • General

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