The Annals of Statistics

Asymptotic Theory for Nested Case-Control Sampling in the Cox Regression Model

Larry Goldstein and Bryan Langholz

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Abstract

By providing a probabilistic model for nested case-control sampling in epidemiologic cohort studies, consistency and asymptotic normality of the maximum partial likelihood estimator of regression parameters in a Cox proportional hazards model can be derived using process and martingale theory as in Andersen and Gill. A general expression for the asymptotic variance is given and used to calculate asymptotic relative efficiencies relative to the full cohort variance in some important special cases.

Article information

Source
Ann. Statist., Volume 20, Number 4 (1992), 1903-1928.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176348895

Digital Object Identifier
doi:10.1214/aos/1176348895

Mathematical Reviews number (MathSciNet)
MR1193318

Zentralblatt MATH identifier
0776.62024

JSTOR
links.jstor.org

Subjects
Primary: 62F12: Asymptotic properties of estimators
Secondary: 62M99: None of the above, but in this section 62D05: Sampling theory, sample surveys

Keywords
Survival analysis cohort sampling martingale censoring efficiency

Citation

Goldstein, Larry; Langholz, Bryan. Asymptotic Theory for Nested Case-Control Sampling in the Cox Regression Model. Ann. Statist. 20 (1992), no. 4, 1903--1928. doi:10.1214/aos/1176348895. https://projecteuclid.org/euclid.aos/1176348895


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