The Annals of Statistics

Large-Sample Properties for a General Estimator of the Treatment Effect in the Two-Sample Problem with Right Censoring

Xiao-Li Meng, Yiannis Bassiakos, and Shaw-Hwa Lo

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Abstract

The estimation of the treatment effect in the two-sample problem with right censoring is of interest in survival analysis. In this article we consider both the location shift model and the scale change model. We establish the large-sample properties of a generalized Hodges-Lehmann type estimator. The strong consistency is established under the minimal possible conditions. The asymptotic normality is also obtained without imposing any conditions on the censoring mechanisms. As a by-product, we also establish a result for the oscillation behavior of the Kaplan-Meier process, which extends the Bahadur result for the empirical process to the censored case.

Article information

Source
Ann. Statist., Volume 19, Number 4 (1991), 1786-1812.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176348371

Digital Object Identifier
doi:10.1214/aos/1176348371

Mathematical Reviews number (MathSciNet)
MR1135149

Zentralblatt MATH identifier
0747.62046

JSTOR
links.jstor.org

Subjects
Primary: 62G05: Estimation
Secondary: 62E20: Asymptotic distribution theory

Keywords
Treatment effect censoring two-sample problem Kaplan-Meier estimators Hodges-Lehmann estimators oscillation of the Kaplan-Meier process

Citation

Meng, Xiao-Li; Bassiakos, Yiannis; Lo, Shaw-Hwa. Large-Sample Properties for a General Estimator of the Treatment Effect in the Two-Sample Problem with Right Censoring. Ann. Statist. 19 (1991), no. 4, 1786--1812. doi:10.1214/aos/1176348371. https://projecteuclid.org/euclid.aos/1176348371


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