Do Preregistration and Preanalysis Plans Reduce p-Hacking and Publication Bias? Evidence from 15,992 Test Statistics and Suggestions for Improvement

Abel Brodeur, Nikolai Cook, Jonathan S. Hartley and Anthony Heyes

Journal of Political Economy Microeconomics, 2024, vol. 2, issue 3, 527 - 561

Abstract: Preregistration is regarded as an important contributor to research credibility. We investigate this by analyzing the pattern of test statistics from the universe of randomized controlled trial studies published in 15 leading economics journals. We draw two conclusions: (a) Preregistration frequently does not involve a preanalysis plan (PAP), or sufficient detail to constrain meaningfully the actions and decisions of researchers after data are collected. Consistent with this, we find no evidence that preregistration in itself reduces p-hacking and publication bias. (b) When preregistration is accompanied by a PAP we find evidence consistent with both reduced p-hacking and reduced publication bias.

Date: 2024
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Working Paper: Do Pre-Registration and Pre-Analysis Plans Reduce p-Hacking and Publication Bias? Evidence from 15,992 Test Statistics and Suggestions for Improvement (2024)
Working Paper: Do Pre-Registration and Pre-Analysis Plans Reduce p-Hacking and Publication Bias?: Evidence from 15,992 Test Statistics and Suggestions for Improvement (2023)
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