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April 2006 Asymptotic theory for the Cox model with missing time-dependent covariate
Jean-François Dupuy, Ion Grama, Mounir Mesbah
Ann. Statist. 34(2): 903-924 (April 2006). DOI: 10.1214/009053606000000038

Abstract

The relationship between a time-dependent covariate and survival times is usually evaluated via the Cox model. Time-dependent covariates are generally available as longitudinal data collected regularly during the course of the study. A frequent problem, however, is the occurence of missing covariate data. A recent approach to estimation in the Cox model in this case jointly models survival and the longitudinal covariate. However, theoretical justification of this approach is still lacking. In this paper we prove existence and consistency of the maximum likelihood estimators in a joint model. The asymptotic distribution of the estimators is given along with a consistent estimator of the asymptotic variance.

Citation

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Jean-François Dupuy. Ion Grama. Mounir Mesbah. "Asymptotic theory for the Cox model with missing time-dependent covariate." Ann. Statist. 34 (2) 903 - 924, April 2006. https://doi.org/10.1214/009053606000000038

Information

Published: April 2006
First available in Project Euclid: 27 June 2006

zbMATH: 1092.62100
MathSciNet: MR2283397
Digital Object Identifier: 10.1214/009053606000000038

Subjects:
Primary: 62N01 , 62N02
Secondary: 62G05

Keywords: asymptotic distribution , consistency , maximum likelihood estimation , missing time-dependent covariate , survival data , Time-dependent Cox model

Rights: Copyright © 2006 Institute of Mathematical Statistics

Vol.34 • No. 2 • April 2006
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