The fragility index is a clinically motivated metric designed to supplement the $p$ value during hypothesis testing. The measure relies on two pillars: selecting cases to have their outcome modified and modifying the outcomes. The measure is interesting but the case selection suffers from a drawback which can hamper its interpretation. This work presents the drawback and a method, the stochastic generalized fragility indices, designed to remedy it. Two examples concerning electoral outcomes and the causal effect of smoking cessation illustrate the method.

翻译：脆弱性指数是一种临床驱动的指标，旨在补充假设检验中的$p$值。该度量依赖于两个核心要素：选择需要修改其结果的情形，以及对这些结果进行修改。这一度量虽有其价值，但情形选择过程存在一个可能影响其解释的缺陷。本文揭示了该缺陷，并提出了一种名为随机广义脆弱性指数的修正方法。通过两个实例——选举结果与戒烟因果效应——对该方法进行了说明。