SUMMARY
This paper describes an approach to proportional hazards analysis of survival data with covariates by parametric modelling of the base‐line hazard in terms of piecewise distributions. Maximum likelihood estimation using GLIM and an iterative method is straightforward. Applications of the method and its use with competing risks are given, in which a two‐piece Weibull fit is clearly superior to the simple Weibull model. Wide generality results from the fact that any given montonic increasing transformation may be applied to the base‐line hazard parameter. It can be expected that piecewise models of this kind will usefully describe many proportional hazards survival processes involving changepoints at which the ruling conditions suddenly alter.
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