Introducing the Event-Adjusted Rank Sum (EARS) Test: A Simple Approach to Survival Analysis Independent of Proportional Hazards.

ABSTRACT:

Background

Survival analyses often violate the proportional hazards (PH) assumption, compromising the validity of widely used statistical tests such as the log-rank test and Cox regression. To address this limitation, we introduce the event-adjusted rank sum (EARS) test, a nonparametric method designed to provide robust time-to-event data analysis without relying on PH.

Materials and methods

The EARS test adjusts survival times by dividing each event time by the proportion of events within its respective group. These adjusted survival times are then compared using the Kruskal-Wallis test. To account for censoring, the resulting p value is adjusted based on the overall proportion of censored observations. We validated the EARS test through simulations involving 1000 co

SUBMITTER: Stalhammar G 

PROVIDER: S-EPMC12624226 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature