With regards to the Intercept(s), I would say "No". Leave them in the model, even if they are not statistically significant. (I expect others to disagree with this, but that is my position on the matter) You might want to read "Analysis of Messy Data, Volume 1, Designed Experiments" by Milliken and Johnson. Even though yours is not a designed experiment, they talk about relevant issues in Chapter 9. In fact, they speak of the "Means Model", which is a distinctly different parameterization than the model you get through SAS. In the "Means Model", all these issues go away. There is a distinct coefficient for the intercept of Group A, and a distinct coefficient for the intercept of Group B. And then, it doesn't matter whether you set A to be 0 and B to be 1, or the other way around.
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