Extreme value regression models: a useful reparameterization for the survival function

In this paper, we consider some aspects of accurate approximate inferences for the survival function at a specifed time t 0 , considering extreme value regression models using a modified form of reparameterization proposed by Guerrero and Johnson, and exploring a non-normality measure for likelihood functions and posterior densities introduced by Kass and Slate. We illustrate the proposed methodology, considering a lifetime data set with two treatments introduced by Lee.