Extended Hazard Regression Model for Reliability and Survival Analysis

被引:30
作者
Louzada-Neto F. [1 ]
机构
[1] Department of Statistics, University of Oxford, Oxford, OX1 3TG
关键词
Hazard regression models; Maximum likelihood estimation; Nonconstant spread parameter; Simulation; Weibull distribution;
D O I
10.1023/A:1009606229786
中图分类号
学科分类号
摘要
We propose an extended hazard regression model which allows the spread parameter to be dependent on covariates. This allows a broad class of models which includes the most common hazard models, such as the proportional hazards model, the accelerated failure time model and a proportional hazards/accelerated failure time hybrid model with constant spread parameter. Simulations based on sub-classes of this model suggest that maximum likelihood performs well even when only small or moderate-size data sets are available and the censoring pattern is heavy. The methodology provides a broad framework for analysis of reliability and survival data. Two numerical examples illustrate the results.
引用
收藏
页码:367 / 381
页数:14
相关论文
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