Diagnostics in logistic regression models

In this paper we study the diagnostics of a logistic regression model using the deletion of observation technique. The model is fitted using the maximum likelihood method and the changes in the estimates and the deviance are observed when the model is refitted after deleting an observation. Expressions are derived so that it is not necessary to re-run the regression after each deletion, thereby considerably saving the computational time.