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March, 1988 Asymptotic Distribution Theory and Efficiency Results for Case-Cohort Studies
Steven G. Self, Ross L. Prentice
Ann. Statist. 16(1): 64-81 (March, 1988). DOI: 10.1214/aos/1176350691

Abstract

A case-cohort design was recently proposed [Prentice (1986)] as a means of reducing cost in large epidemiologic cohort studies. A "pseudolikelihood" procedure was described for relative risk regression parameter estimation. This procedure involves covariate data only on subjects who develop disease and on a random subset of the entire cohort. In contrast, the usual partial likelihood estimation procedure requires covariate histories on the entire cohort. Accordingly, a case-cohort design may affect cost saving, particularly with large cohorts and infrequent disease occurrence. Asymptotic distribution theory for such pseudolikelihood estimators, along with that for corresponding cumulative failure rate estimators, are presented here. Certain asymptotic efficiency expressions relative to full-cohort estimators are developed and tabulated in situations of relevance to the design of large-scale disease prevention trials. The theoretical developments make use of martingale convergence results and finite population convergence results.

Citation

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Steven G. Self. Ross L. Prentice. "Asymptotic Distribution Theory and Efficiency Results for Case-Cohort Studies." Ann. Statist. 16 (1) 64 - 81, March, 1988. https://doi.org/10.1214/aos/1176350691

Information

Published: March, 1988
First available in Project Euclid: 12 April 2007

zbMATH: 0666.62108
MathSciNet: MR924857
Digital Object Identifier: 10.1214/aos/1176350691

Subjects:
Primary: 62E20
Secondary: 60G15, 62G05

Rights: Copyright © 1988 Institute of Mathematical Statistics

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Vol.16 • No. 1 • March, 1988
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