The Annals of Statistics

Some New Estimators for Cox Regression

Peter Sasieni

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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.

Article information

Source
Ann. Statist., Volume 21, Number 4 (1993), 1721-1759.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176349395

Digital Object Identifier
doi:10.1214/aos/1176349395

Mathematical Reviews number (MathSciNet)
MR1245766

Zentralblatt MATH identifier
0797.62020

JSTOR
links.jstor.org

Subjects
Primary: 62F12: Asymptotic properties of estimators
Secondary: 62F35: Robustness and adaptive procedures 62G05: Estimation

Keywords
Case-cohort contiguity Cox model influence function partial likelihood robust estimators survival analysis

Citation

Sasieni, Peter. Some New Estimators for Cox Regression. Ann. Statist. 21 (1993), no. 4, 1721--1759. doi:10.1214/aos/1176349395. https://projecteuclid.org/euclid.aos/1176349395


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