Identification of Prognostic Factors Related to Survival Time: Cox Proportional Hazards Model

  1. Elisa T. Lee and
  2. John Wenyu Wang

Published Online: 30 JUN 2003

DOI: 10.1002/0471458546.ch12

Statistical Methods for Survival Data Analysis, Third Edition

Statistical Methods for Survival Data Analysis, Third Edition

How to Cite

Lee, E. T. and Wang, J. W. (2003) Identification of Prognostic Factors Related to Survival Time: Cox Proportional Hazards Model, in Statistical Methods for Survival Data Analysis, Third Edition, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/0471458546.ch12

Author Information

  1. Department of Biostatistics and Epidemiology and Center for American Indian Health Research, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA

Publication History

  1. Published Online: 30 JUN 2003
  2. Published Print: 4 APR 2003

ISBN Information

Print ISBN: 9780471369974

Online ISBN: 9780471458548

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Keywords:

  • prognostic factors;
  • survival time;
  • identification;
  • Cox proportional hazards model;
  • partial likelihood function;
  • significant covariates identification;
  • survivorship function;
  • estimation;
  • covariates;
  • adequacy assessment

Summary

In this chapter we discuss a most commonly used model, the Cox (1972) proportional hazards model, and its related statistical inference. This model does not require knowledge of the underlying distribution. The hazard function in this model can take on any form, including that of a step function, but the hazard functions of different individuals are assumed to be proportional and independent of time. The usual likelihood function is replaced by the partial likelihood function. The important fact is that the statistical inference based on the partial likelihood function is similar to that based on the likelihood function. The chapter concludes with a problem solving section.