Modelling converging hazards in survival analysis

被引:4
作者
Barker, P [1 ]
Henderson, R [1 ]
机构
[1] Univ Lancaster, Dept Math & Stat, Lancaster LA1 4YW, England
基金
英国医学研究理事会;
关键词
converging hazards; E-M algorithm; gamma frailty; local likelihood; semi-parametric;
D O I
10.1023/B:LIDA.0000036392.68675.7f
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The Cox proportional hazards model has become the standard model for survival analysis. It is often seen as the null model in that"... explicit excuses are now needed to use different models'' (Keiding, Proceedings of the XIXth International Biometric Conference, Cape Town, 1998). However, converging hazards also occur frequently in survival analysis. The Burr model, which may be derived as the marginal from a gamma frailty model, is one commonly used tool to model converging hazards. We outline this approach and introduce a mixed model which extends the Burr model and allows for both proportional and converging hazards. Although a semi-parametric model in its own right, we demonstrate how the mixed model can be derived via a gamma frailty interpretation, suggesting an E - M fitting procedure. We illustrate the modelling techniques using data on survival of hospice patients.
引用
收藏
页码:263 / 281
页数:19
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