Thought about this more overnight. This sounds like a job for PROC CANDISC.  From the documentation: Given a classification variable and several quantitative variables, the CANDISC procedure derives canonical variables, which are linear combinations of the quantitative variables that summarize between-class variation in much the same way that principal components summarize total variation.   The example in the documentation ought to point you in the right direction, and the graphic generated should help with interpretation. Since the canonical variables are constructed based on both within and between associations, any time dependency in your X variables should be accounted for (i.e, they don't have to be independent variables).   SteveDenham ... View more