How to interpret hazard ratios

Jonathan W. Bartlett; Dominic Magirr; Tim P. Morris

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arXiv · 2601.09571

How to interpret hazard ratios

Jonathan W. Bartlett·Dominic Magirr·Tim P. Morris

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Abstract

The hazard ratio, typically estimated using Cox's famous proportional hazards model, is the most common effect measure used to describe the association or effect of a covariate on a time-to-event outcome. In recent years the hazard ratio has been argued by some to lack a causal interpretation, even in randomised trials, and even if the proportional hazards assumption holds. This is concerning, not least due to the ubiquity of hazard ratios in analyses of time-to-event data. We review these criticisms, describe how we think hazard ratios should be interpreted, and argue that they retain a valid causal interpretation. Nevertheless, alternative measures may be preferable to describe effects of exposures or treatments on time-to-event outcomes.

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Jonathan W. Bartlett, Dominic Magirr, Tim P. Morris. 2026-01-14. How to interpret hazard ratios. https://arxiv.org/abs/2601.09571

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