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We develop the theory of hypothesis testing based on the e-value, a notion of evidence that, unlike the p-value, allows for effortlessly combining results from several studies in the common scenario where the decision to perform a new study may depend on previous outcomes.
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Blakeley B. McShane, David Gal, Andrew Gelman, Christian Robert, and Jennifer L. Tackett · 2019
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Likelihood, replicability and robbins’ confidence sequences
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Accumulation bias in meta-analysis: the need to consider time in error control
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Game-Theoretic Probability: Theory and Applications to Prediction, Science and Finance
G. Shafer and V. Vovk · 2019
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Reuben Adams · 2020
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Minimum Description Length revisited
P. Grünwald and T. Roos · 2020
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