Example 3.10

Key words: multinomial logit model, logistic regression, ARTMAP neu- ral network, economic choice,

In this study, we used four machine-learning methods, namely Kernel Logistic Regression (KLR), Radial Basis Function Classifier (RBFC), Multinomial Naïve Bayes (NBM), and

We showed in Section 3.3 that when one fits the binary logistic regression model containing a single dichotomous covariate, that the estimate of the coefficient is equal to the log of

Univariate and multivariate logistic regression analysis was performed for CIR with the following co-variables: colonoscopy category (pa- tients in routine clinics, primary

Multivariable logistic regression model exploring the association between pre-operative isolation and postoperative pulmonary complications, only for patients who underwent surgery in

Univariate Multinomial Logistic regression analysis was used to analyze the effects of univariate variables such as gender; income, age and education on the “beliefs” about paying

Logistic regression model (LRM), which is the most com- monly used for a binary outcome, was applied to investi- gate the effect of main predictors (work/study, housework, family,

Among respondents residing in other (non-metropolitan) areas of Russia, the multivariable logistic regression model showed that, in addition to visited sex-related venues