From Replication Rates to Replication Evidence

Repeating original studies using existing data (reproducibility) or new data (replicability) is key to improving the credibility of scientific results. Here, we focus on replications, which can be broadly categorized into direct replications—testing the original hypothesis in new data using the original analysis and design—and conceptual replications—testing the original hypothesis in new data using an alternate analysis and/or design. While encouraging replications is important, increasing their visibility and impact is equally crucial. Large-scale replication projects have generated valuable insights into the overall level of replicability across fields, but they typically emphasize aggregate estimates. We argue that this focus obscures the informational value of individual replication studies. Each replication provides independent evidence for updating beliefs about the likelihood that the underlying hypothesis is true and the magnitude of the effect. Publishing and disseminating individual replications as standalone contributions can therefore enhance their role in the cumulative advancement of scientific knowledge.