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Bayesian Hypothesis Testing in Two-Arm Trials with Dichotomous Outcomes

机译:具有二分结果的两臂试验中的贝叶斯假设检验

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摘要

This article is motivated by an interest in comparing inferences made when using a Bayesian or frequentist statistical approach. The article addresses the study of one-sided superiority and noninferiority Bayesian tests. These tests are stated in terms of the posterior probability that the null hypothesis is true for the binomial distribution and in terms of onesided credible limits. We restrict our considerations to conjugate beta priors with integer parameters. Under this assumption, the posterior probabilities of tested hypotheses can be transformed into the frequentist probabilities of Bernoulli trials with an adjusted number of events and population sizes. The method resembles a standard frequentist problem formulation. By using an appropriate choice of prior parameters, the posterior probabilities of the null hypothesis can be made smaller or larger than the p-values of frequentist tests.
机译:本文的动机是希望比较使用贝叶斯统计或频繁统计的方法得出的推论。本文介绍了单方面优势和非劣性贝叶斯测试的研究。这些检验是根据零假设对二项式分布成立的后验概率和单方面可信极限来表示的。我们将考虑的范围限制为使用整数参数将beta先验共轭。在此假设下,经过检验的假设的后验概率可以转换为伯努利试验的频繁概率,其中事件和种群的数量经过调整。该方法类似于标准的常客问题表述。通过使用适当的先验参数选择,可以使原假设的后验概率小于或小于常验检验的p值。

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