I'm currently trying to interpret multiple logistic regression with a categorical variable.
Description of variables:
region= the beneficiary’s residential area in the US; a factor with levels northeast, southeast, southwest, northwest.
charges_cat= which takes the value 0 (low) when charges are less than 10000 dollars and the value 1 (high) in all other cases.
bmi= body mass index of primary beneficiary in Kg/m2.
> logm2<-glm(charges_cat~bmi+region, family=binomial) Coefficients: Estimate (Intercept) -0.754605 bmi 0.026294 regionnorthwest -0.180464 regionsoutheast -0.244276 regionsouthwest -0.292365
My interpretation for
b2 = regionnorthwest is:
> exp(-0.180464)  0.8348827
Given that southeast and southwest regions (dummy variables) and also
fixed, the odds of charges being more than 10000 dollars is 16.51% lower than the
odds of charges being more than 10000 dollars for a beneficiary who lives in the
northeast region of the US.
My question is: in multiple logistic regression should I state the factor levels of the
region are fixed, such as “southeast and southwest regions are fixed.” or there is no need to state the dummy variables of the
Also, any other way to interpret