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JAMA Guide to Statistics and Methods
March 13, 2020

Why Test for Proportional Hazards?

Author Affiliations
  • 1Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
  • 2Department of Biostatistics, Oslo Centre for Biostatistics and Epidemiology, University of Oslo, Oslo, Norway
  • 3Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
  • 4Harvard-MIT Division of Health Sciences and Technology, Boston, Massachusetts
JAMA. Published online March 13, 2020. doi:10.1001/jama.2020.1267

The Cox proportional hazards model, introduced in 1972,1 has become the default approach for survival analysis in randomized trials. The Cox model estimates the ratio of the hazard of the event or outcome of interest (eg, death) between 2 treatment groups. Informally, the hazard at any given time is the probability of experiencing the event of interest in the next interval among individuals who had not yet experienced the event by the start of the interval. Because the Cox model requires the hazards in both groups to be proportional, researchers are often asked to “test” whether hazards are proportional.

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