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June, 1992 Asymptotic Normality of the `Synthetic Data' Regression Estimator for Censored Survival Data
Mai Zhou
Ann. Statist. 20(2): 1002-1021 (June, 1992). DOI: 10.1214/aos/1176348667

Abstract

This article studies the large sample behavior of the censored data least squares estimator derived from the synthetic data method proposed by Leurgans and Zheng. The asymptotic distributions are derived by representing the estimator as a martingale plus a higher-order remainder term. Recently developed counting process techniques are used. The results are then compared to the censored regression estimator of Koul, Susarla and Van Ryzin.

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Mai Zhou. "Asymptotic Normality of the `Synthetic Data' Regression Estimator for Censored Survival Data." Ann. Statist. 20 (2) 1002 - 1021, June, 1992. https://doi.org/10.1214/aos/1176348667

Information

Published: June, 1992
First available in Project Euclid: 12 April 2007

zbMATH: 0748.62024
MathSciNet: MR1165603
Digital Object Identifier: 10.1214/aos/1176348667

Subjects:
Primary: 62G10
Secondary: 62N05, 62P10

Rights: Copyright © 1992 Institute of Mathematical Statistics

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Vol.20 • No. 2 • June, 1992
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