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A semiparametric generalized proportional hazards model for right-censored data

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  • M. Avendaño
  • M. Pardo

Abstract

We introduce a flexible family of semiparametric generalized logit-based regression models for survival analysis. Its hazard rates are proportional as the Cox model, but its relative risk related to a covariate is different for the values of the other covariates. The method of partial likelihood approach is applied to estimate its parameters in presence of right censoring and its asymptotic normality is established. We perform a simulation study to evaluate the finite-sample performance of these estimators. This new family of models is illustrated with lung cancer data and compared with Cox model. The importance of the conclusions obtained from the relative risk is pointed out. Copyright The Institute of Statistical Mathematics, Tokyo 2016

Suggested Citation

  • M. Avendaño & M. Pardo, 2016. "A semiparametric generalized proportional hazards model for right-censored data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(2), pages 353-384, April.
    • Handle: RePEc:spr:aistmt:v:68:y:2016:i:2:p:353-384
    DOI: 10.1007/s10463-014-0496-3
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    References listed on IDEAS

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    1. Devarajan, Karthik & Ebrahimi, Nader, 2011. "A semi-parametric generalization of the Cox proportional hazards regression model: Inference and applications," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 667-676, January.
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