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Comparing first hitting time and proportional hazards regression models

Author

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  • D. Stogiannis
  • C. Caroni
  • C. E. Anagnostopoulos
  • I. K. Toumpoulis

Abstract

Cox's widely used semi-parametric proportional hazards (PH) regression model places restrictions on the possible shapes of the hazard function. Models based on the first hitting time (FHT) of a stochastic process are among the alternatives and have the attractive feature of being based on a model of the underlying process. We review and compare the PH model and an FHT model based on a Wiener process which leads to an inverse Gaussian (IG) regression model. This particular model can also represent a “cured fraction” or long-term survivors. A case study of survival after coronary artery bypass grafting is used to examine the interpretation of the IG model, especially in relation to covariates that affect both of its parameters.

Suggested Citation

  • D. Stogiannis & C. Caroni & C. E. Anagnostopoulos & I. K. Toumpoulis, 2011. "Comparing first hitting time and proportional hazards regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(7), pages 1483-1492, June.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:7:p:1483-1492
    DOI: 10.1080/02664763.2010.505954
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    References listed on IDEAS

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