Relaxing the independent censoring assumption in the Cox proportional hazards model using multiple imputation

Stat Med. 2014 Nov 30;33(27):4681-94. doi: 10.1002/sim.6274. Epub 2014 Jul 25.


The Cox proportional hazards model is frequently used in medical statistics. The standard methods for fitting this model rely on the assumption of independent censoring. Although this is sometimes plausible, we often wish to explore how robust our inferences are as this untestable assumption is relaxed. We describe how this can be carried out in a way that makes the assumptions accessible to all those involved in a research project. Estimation proceeds via multiple imputation, where censored failure times are imputed under user-specified departures from independent censoring. A novel aspect of our method is the use of bootstrapping to generate proper imputations from the Cox model. We illustrate our approach using data from an HIV-prevention trial and discuss how it can be readily adapted and applied in other settings.

Keywords: Schoenfeld residuals; bootstrapping; informative censoring; multiple imputation; sensitivity analysis; survival analysis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acyclovir
  • Adolescent
  • Adult
  • Antiviral Agents
  • Bias*
  • Biometry / methods
  • Computer Simulation
  • Female
  • HIV Infections / prevention & control
  • Herpes Genitalis / drug therapy
  • Herpesvirus 2, Human
  • Humans
  • Monte Carlo Method
  • Proportional Hazards Models*
  • Randomized Controlled Trials as Topic
  • Regression Analysis
  • Tanzania
  • Young Adult


  • Antiviral Agents
  • Acyclovir