Local partial-likelihood estimation for lifetime data

Jianqing Fan, Huazhen Lin, Yong Zhou

Research output: Contribution to journalArticlepeer-review

75 Scopus citations

Abstract

This paper considers a proportional hazards model, which allows one to examine the extent to which covariates interact nonlinearly with an exposure variable, for analysis of lifetime data. A local partial-likelihood technique is proposed to estimate nonlinear interactions. Asymptotic normality of the proposed estimator is established. The baseline hazard function, the bias and the variance of the local likelihood estimator are consistently estimated. In addition, a one-step local partial-likelihood estimator is presented to facilitate the computation of the proposed procedure and is demonstrated to be as efficient as the fully iterated local partial-likelihood estimator. Furthermore, a penalized local likelihood estimator is proposed to select important risk variables in the model. Numerical examples are used to illustrate the effectiveness of the proposed procedures.

Original languageEnglish (US)
Pages (from-to)290-325
Number of pages36
JournalAnnals of Statistics
Volume34
Issue number1
DOIs
StatePublished - Feb 2006

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Keywords

  • Local partial likelihood
  • One-step estimation
  • Proportional hazards model
  • Variable selection
  • Varying coefficient

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