Multinomial Logistic Regression Table. The traditional 05 criterion of statistical significance was employed for all tests. Multinomial logistic regression models how multinomial response variable y depends on a set of k explanatory variables x x 1 x 2 dots x k.
In multinomial logistic regression however these are pseudo r 2 measures and there is more than one although none are easily interpretable. When i try to present the results using gtsummary package. An important feature of the multinomial logit model is that it estimates k 1 models where k is the number of levels of the outcome variable.
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In statistics multinomial logistic regression is a classification method that generalizes logistic regression to multiclass problems i e. Multinomial logistic regression tables 1 1 and 1 2 showed how the probability of voting sv or ap depends on whether respondents classify themselves as supporters or opponents of the current tax levels on high incomes. An important feature of the multinomial logit model is that it estimates k 1 models where k is the number of levels of the outcome variable. Viewed 126 times 3.
