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Piecewise Cox models with right-censored data

  • George Y.C. Wong
  • , Michael P. Osborne
  • , Qinggang Diao
  • , Qiqing Yu

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

We study a general class of piecewise Cox models. We discuss the computation of the semi-parametric maximum likelihood estimates (SMLE) of the parameters, with right-censored data, and a simplified algorithm for the maximum partial likelihood estimates (MPLE). Our simulation study suggests that the relative efficiency of the PMLE of the parameter to the SMLE ranges from 96% to 99.9%, but the relative efficiency of the existing estimators of the baseline survival function to the SMLE ranges from 3% to 24%. Thus, the SMLE is much better than the existing estimators.

Original languageEnglish
Pages (from-to)7894-7908
Number of pages15
JournalCommunications in Statistics: Simulation and Computation
Volume46
Issue number10
DOIs
StatePublished - Nov 26 2017

Keywords

  • Cox model
  • Semi-parametric MLE
  • Time-dependent covariates

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