Abstract
Diagnostic methods for multinomial response regression methods are developed as an extension of the regression diagnostic procedure introduced by Pregibon for the case of the binomial logistic regression. For multinomial responses, there exist various indices of association, such as multinomial logit, cumulative logit, adjacent logit, and so on, according to the nominal or ordinal nature of the responses and concepts of the ordering. Regression models are used to reveal the relations of a designated index and possible explanatory variables. We develop diagnostic tools for these regression problems of moderately wide range and evaluate their usefulness and limitations via the applications of the diagnostics for the analyses of a few published data sets.
