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Optimal partitioning for the proportional hazards model

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  • Usha Govindarajulu
  • Thaddeus Tarpey

Abstract

This paper discusses methods for clustering a continuous covariate in a survival analysis model. The advantages of using a categorical covariate defined from discretizing a continuous covariate (via clustering) is (i) enhanced interpretability of the covariate's impact on survival and (ii) relaxing model assumptions that are usually required for survival models, such as the proportional hazards model. Simulations and an example are provided to illustrate the methods.

Suggested Citation

  • Usha Govindarajulu & Thaddeus Tarpey, 2022. "Optimal partitioning for the proportional hazards model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(4), pages 968-987, March.
    • Handle: RePEc:taf:japsta:v:49:y:2022:i:4:p:968-987
    DOI: 10.1080/02664763.2020.1846690
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