Modelling paired survival data with covariates

W. J. Huster, R. Brookmeyer, S. G. Self

Research output: Contribution to journalArticlepeer-review

Abstract

The objective of this paper is to consider the parametric analysis of paired censored survival data when additional covariate information is available, as in the Diabetic Retinopthy Study, which assessed the effectiveness of laser photocoagulation in delaying loss of visual acuity. Our first approach is to extend the fully parametric model of Clayton (1978, Biometrika 65, 141-151) to incorporate covariate information. Our second approach is to obtain parameter estimates from an independence working model together with robust variance estimates. The approaches are compared in terms of efficiency and computational considerations. A fundamental consideration is choosing a strategy for the analysis of paired survival data is whether the correlation within a pair is a nuisance parameter or a parameter of intrinsic scientific interest. The approaches are illustrated with the Diabetic Retinopathy Study.

Original languageEnglish (US)
Pages (from-to)145-156
Number of pages12
JournalBiometrics
Volume45
Issue number1
DOIs
StatePublished - Jan 1 1989

ASJC Scopus subject areas

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

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