This is more a general regression question than specific to sas procs...
Let's say I'm trying to create a model that predicts how much my customers are likely to spend at my store. But looking at my existing customers, I have a hunch that customers who have bought product X are different than those who have bought product Y.
In other words, if I were to build a model from product X customers, the final variables and coefficients could be very different from the model built from product Y customers.
Do I have to build a separate model for each customer segment and somehow blend the results? Or is there a way to build one model that somehow factors in the differences?
In the classic regression sense, you can do this with interaction terms in one model.
As a concrete example, say that X=baby diapers and Y=Viagra. So, you'd expect X-people to be mostly younger and female and the Y-people to be mostly older and male. If X and Y are 0/1 coded, a model might look something like