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Local likelihood with time-varying additive hazards model

  • Hui Li*
  • , Guosheng Yin
  • , Yong Zhou
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The authors propose the local likelihood method for the time-varying coefficient additive hazards model. They use the Newton-Raphson algorithm to maximize the likelihood into which a local polynomial expansion has been incorporated. They establish the asymptotic properties for the time-varying coefficient estimators and derive explicit expressions for the variance and bias. The authors present simulation results describing the performance of their approach for finite sample sizes. Their numerical comparisons show the stability and efficiency of the local maximum likelihood estimator. They finally illustrate their proposal with data from a laryngeal cancer clinical study.

Original languageEnglish
Pages (from-to)321-337
Number of pages17
JournalCanadian Journal of Statistics
Volume35
Issue number2
DOIs
StatePublished - Jun 2007
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Additive model
  • Asymptotic normality
  • Censored data
  • Local polynomial
  • Maximum likelihood
  • Nonparametric estimation

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