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Assessing replicability with the sceptical p-value: Type-I error control and sample size planning
Charlotte Micheloud, Fadoua Balabdaoui, Leonhard Held
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We study a statistical framework for replicability based on a recently proposed quantitative measure of replication success, the sceptical p-value. A recalibration is proposed to obtain exact overall Type-I error control if the effect is null in both studies and additional bounds on the partial and conditional Type-I error rate, which represent the case where only one study has a null effect. The approach avoids the double dichotomization for significance of the two-trials rule and has larger project power to detect existing effects over both studies in combination. It can also be used for power calculations and requires a smaller replication sample size than the two-trials rule for already convincing original studies. We illustrate the performance of the proposed methodology in an application to data from the Experimental Economics Replication Project.
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