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In this paper, we consider the problem of selecting the optimal sample size by controlling the risk of errors in statistical hypothesis testing. Bayesian versions of the frequentist Type I and Type II error probabilities can be obtained by exploiting the two-priors approach. The criterion we consider is based on the control of a weighted average of both errors, that allows to modulate the contribution of each error in the determination of the sample size. The procedure is described by considering a two-arm superiority trial based on binary data.

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Sample Size Requirements to Control Bayesian Error Probabilities in Superiority Trials

  • 会议论文

  • 发表日期：

    2025年

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  • Susanna Gentile,
  • Valeria Sambucini

摘要

In this paper, we consider the problem of selecting the optimal sample size by controlling the risk of errors in statistical hypothesis testing. Bayesian versions of the frequentist Type I and Type II error probabilities can be obtained by exploiting the two-priors approach. The criterion we consider is based on the control of a weighted average of both errors, that allows to modulate the contribution of each error in the determination of the sample size. The procedure is described by considering a two-arm superiority trial based on binary data.