Possibilistic logistic regression for fuzzy categorical response data

A new possibilistic logistic regression is investigated, which can be used in cases where the explanatory variables are crisp observations but the values of the response variable are non-precise and are measured by linguistic terms. For evaluating the model, a goodness-of-fit criterion which is called the mean of capability index is employed. A numerical example in a real clinical study about child´s appetite status is given to explain the method.