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.
Publié le : 1994-06-14
Classification:
Right censored data,
rank tests,
Kendall's tau,
information bound,
monotonicity,
Kaplan-Meier estimator,
62G05,
62J05,
62E20,
62E25
@article{1176325493,
author = {Fygenson, Mendel and Ritov, Ya'acov},
title = {Monotone Estimating Equations for Censored Data},
journal = {Ann. Statist.},
volume = {22},
number = {1},
year = {1994},
pages = { 732-746},
language = {en},
url = {http://dml.mathdoc.fr/item/1176325493}
}
Fygenson, Mendel; Ritov, Ya'acov. Monotone Estimating Equations for Censored Data. Ann. Statist., Tome 22 (1994) no. 1, pp. 732-746. http://gdmltest.u-ga.fr/item/1176325493/