Say for the sake of argument I have a categorical variable called race. The variable has white, black, and Asian levels. I make two dummies (dummy variables) White and Asian (for variable white if 1 you are white for 0 you are not; it is the same logic for the dummy Asian - if 1 you are Asian 0 then you are not). So black is the base variable, aka reference. The dependent variable is weekly income - I have 50 plus predictors of which the two dummies are two. Say I get an effect size of 100 for white. That means that if you are white you earn a hundred dollars more than if you are black a week controlling for the other variables. But what my audience really wants to know is controlling for the other variables what is the difference between being white and not white in income not between white and black or any reference group.
I have heard that this can be done, perhaps by comparing to a grand mean,effect coding?, but I know very little about this.