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In the multinomial logit model we assume that the log-odds of each response Estimation of the parameters of this model by maximum likelihood proceeds. The loglinear model describes the joint distribution of all the variables, whereas the logistic model describes only the conditional distribution of the When categories are unordered, Multinomial Logistic regression is one often-used strategy. Mlogit models are a straightforward extension of logistic models. Maximum likelihood is the most common estimation used for multinomial logistic regression. And, as with logistic regression, model fit tests,Multinomial logistic regression (often just called 'multinomial regression') is used to predict a nominal dependent variable given one or more independent