Can the Replication Rate Tell Us About Selective Publication? - Patrick Vu (Institute for Replication (I4R), 2022)
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.
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