In the dataset I have, there's one categorical variable (A) containing multiple levels. Due to multiple reasons, I want to use continuous variables only for modeling. I feel two other continuous variables (B, C) combined should be good proxies of A. In other words, I want to prove B and C combined are significantly different among levels in A.
So far, I have used MANOVA and got pretty good results. However, I feel MANOVA is more designed for testing if A has an effect on B and C, and here I don't have any causality involved. Is MANOVA the way to go?
