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On the implications of proportional hazards assumptions for competing risks modelling

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  • Simon M. S. Lo
  • Ralf A. Wilke
  • Takeshi Emura

Abstract

The assumption of hazard rates being proportional in covariates is widely made in empirical research and extensive research has been done to develop tests of its validity. This paper does not contribute on this end. Instead, it gives new insights on the implications of proportional hazards (PH) modelling in competing risks models. It is shown that the use of a PH model for the cause-specific hazards or subdistribution hazards can strongly restrict the class of copulas and marginal hazards for being compatible with a competing risks model. The empirical researcher should be aware that working with these models can be so restrictive that only degenerate or independent risks models are compatible. Numerical results confirm that estimates of cause-specific hazards models are not informative about patterns in the data generating process.

Suggested Citation

  • Simon M. S. Lo & Ralf A. Wilke & Takeshi Emura, 2025. "On the implications of proportional hazards assumptions for competing risks modelling," Papers 2508.10577, arXiv.org.
    • Handle: RePEc:arx:papers:2508.10577
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    References listed on IDEAS

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    1. Simon M. S. Lo & Ralf A. Wilke, 2010. "A copula model for dependent competing risks," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(2), pages 359-376, March.
    2. Jaroslava Hlouskova & Panagiotis Tsigaris & Anetta Caplanova & Rudolf Sivak, 2017. "A behavioral portfolio approach to multiple job holdings," Review of Economics of the Household, Springer, vol. 15(2), pages 669-689, June.
    3. Keele, Luke, 2010. "Proportionally Difficult: Testing for Nonproportional Hazards in Cox Models," Political Analysis, Cambridge University Press, vol. 18(2), pages 189-205, April.
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