K-sample omnibus non-proportional hazards tests based on right-censored data

Malka Gorfine*, Matan Schlesinger, Li Hsu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

This work presents novel and powerful tests for comparing non-proportional hazard functions, based on sample–space partitions. Right censoring introduces two major difficulties, which make the existing sample–space partition tests for uncensored data non-applicable: (i) the actual event times of censored observations are unknown and (ii) the standard permutation procedure is invalid in case the censoring distributions of the groups are unequal. We overcome these two obstacles, introduce invariant tests, and prove their consistency. Extensive simulations reveal that under non-proportional alternatives, the proposed tests are often of higher power compared with existing popular tests for non-proportional hazards. Efficient implementation of our tests is available in the R package KONPsurv, which can be freely downloaded from CRAN.

Original languageEnglish
Pages (from-to)2830-2850
Number of pages21
JournalStatistical Methods in Medical Research
Volume29
Issue number10
DOIs
StatePublished - 1 Oct 2020

Funding

FundersFunder number
National Institutes of HealthNIH R01CA189532

    Keywords

    • Combined test
    • consistent test
    • crossing hazards
    • non-parametric test
    • permutation test
    • right censoring
    • sample–space partition
    • versatile test

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