Hypothesis testing is a central statistical method in the biomedical sciences. The ongoing debate about the concept of statistical significance and the reliability of null hypothesis significance tests (NHST) and p-values has brought the advent of various Bayesian hypothesis tests as possible alternatives, which often employ the Bayes factor. However, careful calibration of the prior parameters is necessary for the type I error rates or power of these alternatives to be any better. Also, the availability of various Bayesian tests for the same statistical problem leads to the question which test to choose based on which criteria. Recently proposed Bayesian nonparametric two-sample tests are analyzed with regard to their type I error rates and power to detect an effect. Results show that approaches vary substantially in their ability to control the type I and II errors, and it is shown how to select the prior parameters to balance power and type I error control. This allows for prior elicitation and power analyses based on objective criteria like type I and II error rates even when conducting a Bayesian nonparametric two-sample test. Also, it is shown that existing nonparametric Bayesian two-sample tests are adequate only to test for location-shifts. Together, the results provide guidance how to perform a nonparametric Bayesian two-sample test while simultaneously improving the reliability of research.

假设检验是生物医学科学中的核心统计方法。关于统计显着性的概念以及零假设显着性检验 (NHST) 和 p 值的可靠性的持续辩论已经带来了各种贝叶斯假设检验作为可能的替代方案的出现，这些检验通常采用贝叶斯因子。然而，为了使这些替代方案的 I 类错误率或功效更好，必须仔细校准先验参数。此外，针对同一统计问题的各种贝叶斯测试的可用性导致了基于哪个标准选择哪个测试的问题。最近提出的贝叶斯非参数双样本检验分析了它们的 I 类错误率和检测效果的能力。结果表明，这些方法在控制 I 类和 II 类错误的能力方面存在很大差异，并展示了如何选择先验参数来平衡功率和 I 类错误控制。即使在进行贝叶斯非参数双样本检验时，这也允许基于客观标准（如 I 型和 II 型错误率）进行先验启发和功效分析。此外，还表明现有的非参数贝叶斯双样本检验仅适用于测试位置偏移。总之，这些结果为如何执行非参数贝叶斯双样本检验提供了指导，同时提高了研究的可靠性。即使在进行贝叶斯非参数双样本检验时，这也允许基于客观标准（如 I 型和 II 型错误率）进行先验启发和功效分析。此外，还表明现有的非参数贝叶斯双样本检验仅适用于测试位置偏移。总之，这些结果为如何执行非参数贝叶斯双样本检验提供了指导，同时提高了研究的可靠性。即使在进行贝叶斯非参数双样本检验时，这也允许基于客观标准（如 I 型和 II 型错误率）进行先验启发和功效分析。此外，还表明现有的非参数贝叶斯双样本检验仅适用于测试位置偏移。总之，这些结果为如何执行非参数贝叶斯双样本检验提供了指导，同时提高了研究的可靠性。