Two permutation-based methods for simultaneous inference have recently been published on the proportion of active voxels in cluster-wise brain imaging analysis: Notip (Blain et al., 2022) and pARI (Andreella et al., 2023). Both rely on the definition of a critical vector of ordered p-values, chosen from a family of candidate vectors, but differ in how the family is defined: computed from randomization of external data for Notip, and chosen a-priori for pARI. These procedures were compared to other proposals in literature but, due to the parallel publication process, an extensive comparison between the two is missing. We provide such a comparison, highlighting that pARI can outperform Notip if the settings are selected appropriately. However, each method carries different advantages and drawbacks.

翻译：近期，两种基于排列的同步推断方法被提出用于脑影像簇级分析中活跃体素比例的研究：Notip（Blain等人，2022年）和pARI（Andreella等人，2023年）。两种方法均依赖于从候选向量族中选取的有序p值临界向量的定义，但两者在向量族定义方式上存在差异：Notip通过外部数据的随机化计算得出，而pARI则采用先验选择。这些方法已被用于与文献中的其他提议进行比较，但由于并行发表过程，两者之间缺乏全面对比。我们提供了此类比较，并强调若参数设置得当，pARI可优于Notip。然而，每种方法各有优劣。