I normally work with linear regression, but came across a need to use logistic regression. I started with
glm(y ~ x1 + ..., data, family = binomial()). Almost none of my variables were showing large coefs, which is fine.
Just for kicks I ran the same model, but excluded the intercept
glm(y ~ x1 + ... - 1, data, family = binomial()). In this model most of the coefs were large and significant.
My problem is that I don't have too much experience with logistic regression and I am afraid of using this model simply because I don't want to mess up the interpretation. So my question is:
- What is the interpretation of the exponentiated coefficients of a logistic regression model that has no intercept?