Application of Local Influence Diagnostics to the Buckley-James Model

This article reports the development of local influence diagnostics of Buckley-James model consisting of variance perturbation, response variable perturbation and independent variables perturbation. The proposed diagnostics improves the previous ones by taking into account both censored and uncensored data to have a possibility to become an influential observation. Note that, in the previous diagnostics of Buckley-James model, influential observations merely come from uncensored observations in the data set. An example based on the Stanford heart transplant data is used for illustration. The data set with three covariates is considered in an attempt to show how the proposed diagnostics is able to handle more than one covariate, which is a concern to us as it is more difficult to identify peculiar observations in a multiple covariates.