The Annals of Statistics

Monotone Estimating Equations for Censored Data

Mendel Fygenson and Ya'acov Ritov

Full-text: Open access

Abstract

The monotone class rank-test-based estimating equations for regression models with right censored data is considered. We introduce an estimator which is a solution of a monotone estimating equation that is an extension of the Gehan test. The estimator is easy to derive, $\sqrt n$-consistent and asymptotically normal under minimal conditions. All monotone estimating equations are characterized, and a simulation study, which shows that our suggested procedure performs well, is included.

Article information

Source
Ann. Statist. Volume 22, Number 2 (1994), 732-746.

Dates
First available in Project Euclid: 11 April 2007

Permanent link to this document
http://projecteuclid.org/euclid.aos/1176325493

Digital Object Identifier
doi:10.1214/aos/1176325493

Mathematical Reviews number (MathSciNet)
MR1292538

Zentralblatt MATH identifier
0807.62032

JSTOR
links.jstor.org

Subjects
Primary: 62G05: Estimation
Secondary: 62J05: Linear regression 62E20: Asymptotic distribution theory 62E25

Keywords
Right censored data rank tests Kendall's tau information bound monotonicity Kaplan-Meier estimator

Citation

Fygenson, Mendel; Ritov, Ya'acov. Monotone Estimating Equations for Censored Data. Ann. Statist. 22 (1994), no. 2, 732--746. doi:10.1214/aos/1176325493. http://projecteuclid.org/euclid.aos/1176325493.


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