I have one continuous variable (X), a categorical variable (Z; treatment condition with three levels), and a continuous outcome variable (Z). X is an individual difference variable.
I have already figured out how to compare the different treatment conditions for different values of X. For example, for comparing treatment 1 and 2 among individuals scoring low on X (Mean of X at -1 SD = 4.2261), I would write the following:
model y = Z X Z*X;
ESTIMATE 'Z 1 vs 2 at low X' Z -1 1 0 Z*X -4.2261 4.2261 0;
However, I can't figure out how to test whether individuals that score high versus low on X differ in Y, for each level of Z. (e.g., comparing Y scores for low and high X in treatment condition 1; comparing Y scores for low and high X in treatment condition 2 etc).
It usually helps to write out the ESTIMATE statement for each condition that you want to use in a contrast and then take the difference between the coefficients that are involved in that contrast. For instance, for treatment group 1, estimate statements for low and high X would be
estimate "Trt=1, low X"
z 1 0 0
z*x -4.661 0 0;
estimate "Trt=1, high X"
z 1 0 0
z*x 4.661 0 0;
The difference between these two is the effect of interest that you are having trouble constructing. But as presented above, the effect of interest would be:
estimate "Trt=1, high vs low X"
z*x 9.322 0 0;
Just change the label and the last line to reflect the different treatment conditions.