Multinomial Logistic Regression Table. Table 3 shows the multinomial logistic regression model for all coefficients. The traditional 05 criterion of statistical significance was employed for all tests.
Ask question asked 2 months ago. In statistics multinomial logistic regression is a classification method that generalizes logistic regression to multiclass problems i e. Table 2 indicates that the power of the logistic multinomial model was suitable as it correctly classified 45 7 of the known observations and could be expected to project future estimates.
I have a dependent variable with four outcomes.
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. The traditional 05 criterion of statistical significance was employed for all tests. 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. This is also a glm where the random component assumes that the distribution of y is multinomial n mathbf π where mathbf π is a vector with probabilities of success for each.
