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A semiparametric generalized proportional hazards model for right-censored data

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.

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Acknowledgments

This work was supported by research grant MTM2013-40778-R and MAEC-AECID. The authors are grateful to the referees for their valuable comments and proposals which have improved the contents of this paper.

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Correspondence to M. L. Avendaño.

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Avendaño, M.L., Pardo, M.C. A semiparametric generalized proportional hazards model for right-censored data. Ann Inst Stat Math 68, 353–384 (2016). https://doi.org/10.1007/s10463-014-0496-3

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Keywords

  • Survival analysis
  • Proportional hazards
  • Type-I generalized logistic distribution
  • Semiparametric models
  • Profile likelihood
  • Partial likelihood