survHC: Higher Criticism Tests for Non-Proportional Hazard Deviations

Implements omnibus tests for comparing two right-censored survival samples that are powerful against sparse departures from equal hazards, where the hazard difference is concentrated in a small and a priori unknown subset of the follow-up. Exact hypergeometric p-values are computed for each time interval and aggregated with the Higher Criticism statistic of Donoho and Jin (2004) <doi:10.1214/009053604000000265>, or alternatively with the Berk-Jones, Fisher or minimum-p statistics. Global p-values are obtained by permuting group labels, and the intervals driving a detection can be recovered for diagnostic plotting. Tests accept either two samples as vectors or the usual survival formula. The method is described in Kipnis, Galili and Yakhini (2026) <doi:10.1093/biomet/asaf075>, and the companion application note is Kipnis, Galili and Yakhini (2026) <doi:10.48550/arXiv.2610.07268>.

Getting started

Package details

AuthorAlon Kipnis [aut, cre], Ben Galili [aut], Zohar Yakhini [aut]
MaintainerAlon Kipnis <alonkipnis@gmail.com>
LicenseMIT + file LICENSE
Version0.1.0
URL https://github.com/alonkipnis/lifelines-hc/tree/main/R-package/survHC 
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("survHC")

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survHC documentation built on Oct. 22, 2026, 1:06 a.m.