Aggregating dependent signals with heavy-tailed combination tests.

ABSTRACT: Combining dependent [Formula: see text]-values poses a long-standing challenge in statistical inference, particularly when aggregating findings from multiple methods to enhance signal detection. Recently, [Formula: see text]-value combination tests based on regularly-varying-tailed distributions, such as the Cauchy combination test and harmonic mean [Formula: see text]-value, have attracted attention for their robustness to unknown dependence. This paper provides a theoretical and empirical evaluation of these methods under an asymptotic regime where the number of [Formula: see text]-values is fixed and the global test significance level approaches zero. We examine two types of dependence among the [Formula: see text]-values. First, when [Formula: see text]-values are pairwise asymptotical

SUBMITTER: Gui L 

PROVIDER: S-EPMC12570179 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature