The paper introduces the Worst-case Marginal Benefit (WMB) criterion for sample-size design in test-and-roll experiments and shows it yields an optimal m approximately equal to N/3 for Bernoulli and Gaussian outcomes.
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Prior-Free Sample Size Design for Test-and-Roll Experiments
The paper introduces the Worst-case Marginal Benefit (WMB) criterion for sample-size design in test-and-roll experiments and shows it yields an optimal m approximately equal to N/3 for Bernoulli and Gaussian outcomes.