P-Curve and Effect Size: Correcting for Publication Bias Using Only Significant Results

TitleP-Curve and Effect Size: Correcting for Publication Bias Using Only Significant Results
Publication TypeReport
Year of Publication2014
AuthorsNelson, LD, Simonsohn, U, Simmons, JP
Date Published2014/04/27/
PublisherSocial Science Research Network
Place PublishedRochester, NY
Publication Languageeng
ISBN NumberID 2377290
Keywordsp-curve , Publication
AbstractJournals tend to publish only statistically significant evidence, creating a scientific record that markedly overstates the size of effects. We provide a new tool that corrects for this bias without requiring access to nonsignificant results. It capitalizes on the fact that the distribution of significant p-values, p-curve, is a function of the true underlying effect. Researchers armed only with sample sizes and test results of the published findings can correct for publication bias. We validate the technique with simulations and by re-analyzing data from the Many-Labs Replication project. We demonstrate p-curve can arrive at inferences opposite that of existing tools by re-analyzing the meta-analysis of the “choice overload” literature.
URLhttp://papers.ssrn.com/abstract=2377290

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