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Can the Replication Rate Tell Us About Selective Publication?

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  • Vu, Patrick

Abstract

Selective publication is among the most-cited reasons for widespread replication failures. I show in a simple model of the publication process that the replication rate is completely unresponsive to the suppression of insignificant results. I then show that the expected replication rate falls below its intended target owing to issues with common power calculations in replication studies, even in the absence of other factors such as p-hacking or heterogeneous treatment effects. I estimate an empirical model to evaluate if issues with power calculations alone are sufficient to explain the low replication rates observed in large-scale replication studies. The model produces replication rate predictions (using only data from original studies) that are almost identical to observed replication rates in experimental economics and social science. In psychology, the model explains two-thirds of the gap between the replication rate and its intended target. I conclude by discussing alternative measures of replication that are more responsive to selective publication.

Suggested Citation

  • Vu, Patrick, 2022. "Can the Replication Rate Tell Us About Selective Publication?," I4R Discussion Paper Series 3, The Institute for Replication (I4R).
    • Handle: RePEc:zbw:i4rdps:3
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    3. Valentin Amrhein & David Trafimow & Sander Greenland, 2019. "Inferential Statistics as Descriptive Statistics: There Is No Replication Crisis if We Don’t Expect Replication," The American Statistician, Taylor & Francis Journals, vol. 73(S1), pages 262-270, March.
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    Cited by:

    1. Guillaume Coqueret, 2023. "Forking paths in financial economics," Papers 2401.08606, arXiv.org.

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