Diagnostics in a simple correspondence analysis model: An approach based on Cook’s distance for log-linear models

Diagnostics have not received much attention in the literature of simple correspondence analysis models. Since Cook’s distance was defined to identify influential observations of the linear regression model, it has been extended to different models, in particular to log-linear models. In this paper we provide the asymptotic distribution of Cook’s distance of any kind of log-linear models and also a method for diagnostics, based on it. By using Goodman’s RC(K) model as a log-linear model to approximate the ordinary simple correspondence analysis procedure, we follow a Cook’s distance approach to identify influential cells and three examples illustrate the performance of this method.