Analyzing doubly censored data with covariates, with application to AIDS

M. Y. Kim, V. G. De Gruttola, S. W. Lagakos

Research output: Contribution to journalArticle

82 Scopus citations

Abstract

This paper proposes a method for incorporating covariate information in the analysis of survival data when both the time of the originating event and the failure event can be right- or interval-censored. This method generalizes the one-sample estimation results of De Gruttola and Lagakos by allowing the distribution of time between the two events to be a function of covariates under a proportional hazards model. Estimates for the model coefficients, as well as the underlying distributions, are obtained by an iterative fitting procedure based on Turnbull's self-consistency algorithm in combination with the Newton-Raphson algorithm. The method is illustrated with data from a study of hemophiliacs infected with the human immunodeficiency virus.

Original languageEnglish (US)
Pages (from-to)13-22
Number of pages10
JournalBiometrics
Volume49
Issue number1
DOIs
StatePublished - Jan 1 1993
Externally publishedYes

Keywords

  • AIDS
  • Interval censoring
  • Proportional hazards
  • Self-consistency

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'Analyzing doubly censored data with covariates, with application to AIDS'. Together they form a unique fingerprint.

  • Cite this