Hazard regression for interval-censored data with penalized spline

Tianxi Cai, Rebecca Betensky

Research output: Contribution to journalArticle

Abstract

This article introduces a new approach for estimating the hazard function for possibly interval- and right-censored survival data. We weakly parameterize the log-hazard function with a piecewise-linear spline and provide a smoothed estimate of the hazard function by maximizing the penalized likelihood through a mixed model-based approach. We also provide a method to estimate the amount of smoothing from the data. We illustrate our approach with two well-known interval- censored data sets. Extensive numerical studies are conducted to evaluate the efficacy of the new procedure.

Original languageEnglish (US)
Pages (from-to)570-579
Number of pages10
JournalBiometrics
Volume59
Issue number3
DOIs
StatePublished - Sep 1 2003

Fingerprint

Penalized Splines
Interval-censored Data
Hazard Function
Hazard
Splines
Hazards
Regression
Censored Survival Data
Penalized Likelihood
Right-censored Data
Parameterise
Mixed Model
Piecewise Linear
Estimate
Spline
Efficacy
Smoothing
Numerical Study
methodology
Model-based

Keywords

  • Mixed model
  • Proportional hazards
  • Restricted maximum likelihood

ASJC Scopus subject areas

  • Statistics and Probability
  • Medicine(all)
  • Immunology and Microbiology(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

Cite this

Hazard regression for interval-censored data with penalized spline. / Cai, Tianxi; Betensky, Rebecca.

In: Biometrics, Vol. 59, No. 3, 01.09.2003, p. 570-579.

Research output: Contribution to journalArticle

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