Comparing survival experiences of different groups of data is an important issue in several applied problems. A typical example is where one wishes to investigate treatment effects. Here we propose a new Bayesian approach based on restricted mean survival times (RMST). A nonparametric prior is specified for the underlying survival functions: this extends the standard univariate neutral to the right processes to a multivariate setting and induces a prior for the RMST's. We rely on a representation as exponential functionals of compound subordinators to determine closed form expressions of prior and posterior mixed moments of RMST's. These results are used to approximate functionals of the posterior distribution of RMST's and are essential for comparing time--to--event data arising from different samples.

翻译：比较不同数据组的生存经验是若干应用问题中的重要议题。典型案例如治疗效果的探究。本文提出一种基于限制平均生存时间（RMST）的新贝叶斯方法。我们为潜在生存函数设定非参数先验：将标准单变量中立右过程扩展至多元场景，并由此导出RMST的先验分布。借助复合从属过程的指数泛函表示，我们推导出RMST先验与后验混合矩的解析表达式。这些结果可用于近似RMST后验分布的泛函，对比较不同样本产生的生存时间数据具有关键意义。