期刊
BIOMETRIKA
卷 90, 期 2, 页码 341-353出版社
OXFORD UNIV PRESS
DOI: 10.1093/biomet/90.2.341
关键词
accelerated life model; censoring; Gehan statistic; linear programming; rank estimator; survival data; weighted log-rank statistic
A broad class of rank-based monotone estimating functions is developed for the semi-parametric accelerated failure time model with censored observations. The corresponding estimators can be obtained via linear programming, and are shown to be consistent and asymptotically normal. The limiting covariance matrices can be estimated by a resampling technique, which does not involve nonparametric density estimation or numerical derivatives. The new estimators represent consistent roots of the non-monotone estimating equations based on the familiar weighted log-rank statistics. Simulation studies demonstrate that the proposed methods perform well in practical settings. Two real examples are provided.
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