Analysis of Accelerated Hazards Models


Complete text of article in Journal of the American Statistical Association, 95, 608-618, 2000.


The proportional hazards model for survival time data usually assumes that the covariates of interest take constant effect proportionally on an unspecified baseline hazard function. However, it may not be applicable when the assumption of constant proportionality is violated. In a two-arm randomized clinical trial, for example, the treatment is often expected to be fully effective after a certain lag period. Some alternatives, such as the accelerated failure time model, have been developed in the statistical literature. In this article, an accelerated hazard model is introduced when there is a scale change relationship between the hazard functions. An estimating equation is proposed to estimate the parameter semiparametrically. The methodology is demonstrated within a two-sample framework. Several extensions of the model are also considered. Clinical trial data is used to investigate practical usage of the models.


Clinical Trials | Statistical Models | Survival Analysis

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