Preprint: No Need to Choose: Robust Bayesian Meta-Analysis With Competing Publication Bias Adjustment Methods

This post is a synopsis of Bartoš, F, Maximilian M, Wagenmakers E.-J., Doucouliagos H., & Stanley, T D. (2021). No need to choose: Robust Bayesian meta-analysis with competing publication bias adjustment methods. Preprint available at https://doi.org/10.31234/osf.io/kvsp7 Abstract “Publication bias is a ubiquitous threat to the validity of meta-analysis and the accumulation of scientific evidence. In order to estimate and counteract…

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Take Part in a Bayesian Forecasting Study (the Winner Receives €100/$120)

Can you predict the effect sizes of typical psychology experiments? Take part in our survey and find out! The winner earns €100 or about $120. Participants should have at least a rudimentary understanding of statistics and effect sizes.   The survey takes only 15 minutes and you will receive feedback about your performance; pilot testers reported that it is tons…

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