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Predicting replication outcomes in the Many Labs 2 study
- Eskil Forsell
- domenico viganola
- Thomas Pfeiffer
- Johan Almenberg
- Brad Wilson
- Yiling Chen
- Brian A. Nosek
- Magnus Johannesson
- Anna Dreber Almenberg
- David Reinstein
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Description: Understanding and improving reproducibility is crucial for scientific progress. Prediction markets and related methods of eliciting peer beliefs are promising tools to predict replication outcomes. We invited researchers in the field of psychology to judge the replicability of 24 studies replicated in the large scale Many Labs 2 project. We elicited peer beliefs in prediction markets and surveys about two replication success metrics: the probability that the replication yields a statistically significant effect in the original direction (p<0.001), and the relative effect size of the replication. The prediction markets correctly predicted 75% of the replication outcomes, and were highly correlated with the replication outcomes. Survey beliefs were also significantly correlated with replication outcomes, but had higher prediction errors. The prediction markets for relative effect sizes attracted little trading and thus did not work well. The survey beliefs about relative effect sizes performed better and were significantly correlated with observed relative effect sizes. These results suggest that replication outcomes can be predicted and that the elicitation of peer beliefs can increase our knowledge about scientific reproducibility and the dynamics of hypothesis testing.