Evaluating survival model performance: A graphical approach

Micha Mandel*, N. Galai, E. Simchen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


In the last decade, many statistics have been suggested to evaluate the performance of survival models. These statistics evaluate the overall performance of a model ignoring possible variability in performance over time. Using an extension of measures used in binary regression, we propose a graphical method to depict the performance of a survival model over time. The method provides estimates of performance at specific time points and can be used as an informal test for detecting time varying effects of covariates in the Cox model framework. The method is illustrated on real and simulated data using Cox proportional hazard model and rank statistics.

Original languageAmerican English
Pages (from-to)1933-1945
Number of pages13
JournalStatistics in Medicine
Issue number12
StatePublished - 30 Jun 2005


  • Bootstrap
  • Explained variation
  • ROC curve
  • Survival model
  • Time varying effect


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