Two variables, A and
B, interact if the effect of one variable
on the model changes as the other variable changes. That is, the effects
of variables A and B are not additive in the model.
SAS Visual Statistics enables you to create interactions between two or more input
variables, including squared interactions. A squared interaction is the interaction
of a variable with itself. You cannot create squared interactions for category variables.
For an example where interaction terms might be useful, consider a situation where
you are modeling the fuel mileage (MPG) for several cars. Two of your input variables
are engine displacement in liters and engine size (number of cylinders). You expect
that as
either value increases, fuel mileage will suffer. However, if you suspect that the
effects on fuel mileage that are attributable to engine displacement are not constant
across engine size, then you should consider creating the interaction term between
those variables.
SAS Visual Statistics is not limited to creating just
two-way interactions. You can create
n-way
interactions that include an arbitrary number of variables, but not
more than the number of available input variables.
The number of distinct levels for an interaction term is the product of the number
of levels for each variable in the term. Measure variables are treated as if they
contain one level. The number of levels in an interaction term counts against the
maximum number of distinct levels allowed in
regression models.