In this section we extend the concepts from Logistic Regression where we describe how to build and use binary logistic regression models to cases where the dependent variable can have more than two outcomes. Using such models the value of the categorical dependent variable can be predicted from the values of the independent variables.
We first address the categorical case where there is no order to these outcomes (multinomial logistic regression). We then turn our attention the situation where there is order (ordinal logistic regression).
- Basic concepts of multinomial logistic regression
- Finding multinomial logistic regression coefficients
- Real Statistics capabilities
- Ordinal logistic regression