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Type Ⅰ and Ⅱ error rates of Bayesian two-sample tests under preliminary assessment of normality in balanced and unbalanced designs and its influence on the reproducibility of medical research

机译:浅谈平衡和不平衡设计中正常性初步评估Ⅰ型和Ⅱ次误差率及其对医学研究再现性的影响

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Student's two-sample t-test is often used in medical research like randomized controlled trials. To control type I errors, normality of the observed data needs to be assessed. In practice, a two-stage procedure is acknowledged: First, a preliminary test for normality is conducted. If the test is not significant, the two-sample t-test is applied, and else a nonparametric test like Mann-Whitney's U is conducted. It is unknown how Bayesian tests behave under this procedure. A simulation study was conducted to study the error rates of these Bayesian alternatives under preliminary assessment of normality in balanced and unbalanced designs. Results show that Bayesian counterparts yield 50-60% fewer type I errors at the cost of slightly increased type II error rates, and that the two-stage procedure is not recommended in unbalanced Bayesian designs. This makes them an attractive alternative for biomedical research, as decreased power can be overcome by increasing sample size.
机译:学生的两种样品T检验通常用于医学研究,如随机对照试验。 要控制I型错误,需要评估观察数据的正常性。 在实践中,确认了两阶段程序:首先,进行对正常性的初步测试。 如果测试不显着,则施加两个样本T检验,否则进行曼诺 - 惠特尼的UN参数测试。 据了解了贝叶斯测试在此程序下的表现。 进行了仿真研究,以研究初步评估平衡和不平衡设计的初步评估下这些贝叶斯替代品的错误率。 结果表明,贝叶斯同行产量略微增加的II型误差率的成本,较少的I型误差率为50-60%,并且在不平衡的贝叶斯设计中不建议两阶段程序。 这使它们成为生物医学研究的有吸引力的替代方案,因为可以通过增加样品大小来克服降低的功率。

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