Open Access
December, 1993 Some New Estimators for Cox Regression
Peter Sasieni
Ann. Statist. 21(4): 1721-1759 (December, 1993). DOI: 10.1214/aos/1176349395

Abstract

New estimators for Cox regression are considered. Their asymptotic properties, both on and off the model, are established. Corollaries include conditions under which the maximum partial likelihood estimator defines a parameter in the population and the asymptotics of the case-cohort estimator. Robust estimators that minimize the asymptotic variance subject to a bound on the maximal bias on infinitesimal neighborhoods are discussed. The estimators are illustrated with medical data.

Citation

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Peter Sasieni. "Some New Estimators for Cox Regression." Ann. Statist. 21 (4) 1721 - 1759, December, 1993. https://doi.org/10.1214/aos/1176349395

Information

Published: December, 1993
First available in Project Euclid: 12 April 2007

zbMATH: 0797.62020
MathSciNet: MR1245766
Digital Object Identifier: 10.1214/aos/1176349395

Subjects:
Primary: 62F12
Secondary: 62F35 , 62G05

Keywords: Case-cohort , contiguity , Cox model , influence function , partial likelihood , robust estimators , Survival analysis

Rights: Copyright © 1993 Institute of Mathematical Statistics

Vol.21 • No. 4 • December, 1993
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