In this article, we describe a quantitative approach for comparing the reliability or survival functions for two populations. The Bayesian probability of agreement (BPA) quantifies the similarity of the functions in regions of interest in the covariate space while accounting for a user-specified measure of what constitutes a practically important difference. The BPA method can be flexibly used for relationships with any number of covariates and for a variety of parametric models, including Weibull, lognormal and gamma regression. We provide an R Shiny app that allows practitioners to easily use the method without the need to implement the underlying computational details. Three examples from industrial and medical applications illustrate the implementation of the method as well as how to interpret the results from the analysis.

在本文中，我们描述了一种定量方法，用于比较两个人群的可靠性或生存功能。贝叶斯一致概率（BPA）量化了协变量空间中感兴趣区域中函数的相似性，同时考虑了由用户指定的实际差异的度量。BPA方法可以灵活地用于与任意数量的协变量之间的关系以及各种参数模型，包括Weibull，对数正态和伽马回归。我们提供了一个R Shiny应用程序，使从业人员可以轻松地使用该方法，而无需实现基础的计算细节。来自工业和医学应用的三个示例说明了该方法的实现以及如何解释分析结果。