# Transforming Logistic Regression Model

I have a Logistic Regression Model in R

m1 <- glm(walz_vote ~ voter_party + voter_age + voter_college + voter_female +
voter_race + voter_hispanic +voter_urban + voter_county,
data = data, family = "binomial")


Plotting the linear model looks like this, I'm not super familiar with logistic regression, but from what I know the assumptions of the model failed. How would I go about transforming this?

• For logistic regression your response variable should be $\in [0, 1]$, what is yours? – Cameron Chandler Oct 26 at 7:24
• You might have a "factor" displayed as an integer" and that can turn your model to junk quickly. Please duble-check. It looks like you are using 'R', so the 'str(data)' command applied to your data will tell you if voter_party or voter_hispanic is integer or factor. If you are using binomial ink, then your output should also be a factor. I don't see that in the residual. How can you get continuous residual from classifier error? I think "family=binomial" might also work. – EngrStudent Oct 26 at 17:12