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Multinomial Logistic Regression
Multinomial logistic regression

The generalized linear modelling technique of multinomial logistic regression can be used to model unordered categorical response variables. This model can be understood as a simple extension of logistic regression that allows each category of an unordered response variable to be compared to an arbitrary reference category providing a number of logit regression models. A binary logistic regression model compares one dichotomy (e.g. passed–failed, died–survived, etc.), whereas the multinomial logistic regression model compares a number of dichotomies. This procedure outputs a number of logistic regression models that make specific comparisons of the response categories. When there are j categories of the response variable, the model consists of j − 1 logit equations which are fit simultaneously. Multinomial logistic regression is a ...

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