Evaluating survival model performance: a graphical approach

Authors

  • M. Mandel,

    Corresponding author
    1. Department of Health Services Research, Ministry of Health, Jerusalem, Israel
    2. Department of Statistics, The Hebrew University, Jerusalem, Israel
    • Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, U.S.A.
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  • N. Galai,

    1. Department of Health Services Research, Ministry of Health, Jerusalem, Israel
    2. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, U.S.A.
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  • E. Simchen

    1. Department of Health Services Research, Ministry of Health, Jerusalem, Israel
    2. School of Public Health, The Hebrew University-Hadassah Medical School, Jerusalem, Israel
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Abstract

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. Copyright © 2005 John Wiley & Sons, Ltd.

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