Logistic Regression Model Application in Research
Logistic Regression Model for Bank loan Default Selection A logit model (or logistic regression model) is a statistical method used to predict the probability of a binary outcome (like yes/no, success/failure) based on one or more independent variables. It transforms a linear combination of predictors into probabilities between 0 and 1 using the logistic function. Example Imagine a bank wants to predict whether a loan applicant will default: Dependent variable: Default (1 = yes, 0 = no) Independent variables: Income, credit score, age The logit model estimates how these factors influence the probability of default. Let’s build a logit model example for predicting bank loan default using the three independent variables we mentioned: Income, Credit Score, and Age . Example: Bank Default Prediction Model Setup Dependent variable (Y): Default (1 = default, 0 = no default) Independent variables (X): (X_1): Income (in $10...