Multinomial Logistic Regression Equation. Multinomial logistic regression is used to model nominal outcome variables in which the log odds of the outcomes are modeled as a linear combination of the predictor variables. The relative risk is the right hand side linear equation exponentiated leading to the fact that the exponentiated regression coefficients are relative risk ratios.
Multinomial logistic regression is an expansion of logistic regression in which we set up one equation for each logitrelative to the reference outcome expression 3 1. The word polychotomous is sometimes used but this word does not exist when analyzing a polytomous response it s important to note whether the response is ordinal. One might think of these as ways of applying multinomial logistic regression when strata or clusters are apparent in the data.
The logistic regression equation can be represented as equation for logistic regression.
P is ambiguous when there are more than two outcomes. That is it is a model that is used to predict the probabilities of the different possible outcomes of a categorically distributed dependent variable given a set of independent variables. X1 x2 xk set of input features of x. Multinomial logistic regression models polytomous responses.
