Comparing proportional hazards and accelerated failure time models for survival analysis

This paper describes a method proposed for a censored linear regression model that can be used in the context of survival analysis. The method has the important characteristic of allowing estimation and inference without knowing the distribution of the duration variable. Moreover, it does not need the assumption of proportional hazards. Therefore, it can be an interesting alternative to the Cox proportional hazards models when this assumption does not hold. In addition, implementation and interpretation of the results is simple. In order to analyse the performance of this methodology, we apply it to two real examples and we carry out a simulation study. We present its results together with those obtained with the traditional Cox model and AFT parametric models. The new proposal seems to lead to more precise results.

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