Regression with a Polytomous Dependent Variable Regression with a Polytomous Dependent Variable

This chapter describes the use of multinomial logistic regression (also known as polytomous or nominal logistic or logit regression or the discrete choice model), a method for modeling relationships between a polytomous dependent variable and multiple independent variables. Polytomous variables have three or more unordered categories and are often called multicategorical or multinomial (the assumed underlying distribution). The chapter also discusses the testing and presentation of interactions and curvilinear relationships with multinomial logistic regression, as well as the assumptions of the model.