Multinomial logistic regression is a statistical method used to model the relationship between a dependent variable with more than two categories and one or more independent variables. This method extends binary logistic regression to situations where the outcome variable can fall into multiple discrete categories, allowing researchers to understand how the independent variables influence the probabilities of each category outcome. It is particularly useful in situations where the response variable is nominal, meaning the categories have no natural order.
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