I'm still a newbie and need some help for my linear regression model. Here are my models I've created for my regression.
model_1 <- lm(data=Loan, ApplicantIncome ~ Gender)
model_2 <- lm(data=Loan, ApplicantIncome ~ Married)
model_3 <-lm(data=Loan, ApplicantIncome ~ Married * Gender * Dependents)
model_4 <- lm(data=Loan, ApplicantIncome ~ Gender + Married + Dependents + Education)
As you can see, I included a double interaction effect in the regression. Now I'm desperately looking for a method to test the multicollinearity for my model. As I know, we visualized the full model with the vif function, but it seems to be better if I would visualize each model for its own due to the interaction effect. Do you have any suggestions?
Find attached the dataset from kaggle.
Loan Dataset | Kaggle
Thanks in advance!