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February 2009 Proportional hazards models with continuous marks
Yanqing Sun, Peter B. Gilbert, Ian W. McKeague
Ann. Statist. 37(1): 394-426 (February 2009). DOI: 10.1214/07-AOS554

Abstract

For time-to-event data with finitely many competing risks, the proportional hazards model has been a popular tool for relating the cause-specific outcomes to covariates [Prentice et al. Biometrics 34 (1978) 541–554]. This article studies an extension of this approach to allow a continuum of competing risks, in which the cause of failure is replaced by a continuous mark only observed at the failure time. We develop inference for the proportional hazards model in which the regression parameters depend nonparametrically on the mark and the baseline hazard depends nonparametrically on both time and mark. This work is motivated by the need to assess HIV vaccine efficacy, while taking into account the genetic divergence of infecting HIV viruses in trial participants from the HIV strain that is contained in the vaccine, and adjusting for covariate effects. Mark-specific vaccine efficacy is expressed in terms of one of the regression functions in the mark-specific proportional hazards model. The new approach is evaluated in simulations and applied to the first HIV vaccine efficacy trial.

Citation

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Yanqing Sun. Peter B. Gilbert. Ian W. McKeague. "Proportional hazards models with continuous marks." Ann. Statist. 37 (1) 394 - 426, February 2009. https://doi.org/10.1214/07-AOS554

Information

Published: February 2009
First available in Project Euclid: 16 January 2009

zbMATH: 1155.62075
MathSciNet: MR2488357
Digital Object Identifier: 10.1214/07-AOS554

Subjects:
Primary: 62N01
Secondary: 62G20, 62N02, 62N03

Rights: Copyright © 2009 Institute of Mathematical Statistics

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Vol.37 • No. 1 • February 2009
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