Dr. Wicklin:
I am using ORPOL to compute linear and quadratic contrast coefficients to use in PROC Mixed to evaluate treatment responses. I'm applying them to a small test data set with 3 treatments, and 4 observations per treatment. Treatments are unequally spaced levels (0, 120, 480), and the middle treatment (120) has one missing value. I'm using ORPOL as follows:

x1={0 120 480};
w={4 3 4};
x1p=orpol(x1,2,w);

When I apply the weighted coefficients that come directly from the x1p matrix for the linear and quadratic contrasts in Proc Mixed, the contrasts are non-estimable. If I don't weight for missing values, the contrasts are estimable. I noticed that the weighted contrasts don't sum to zero, which I assume is the reason for the non-estimable error. To get the contrasts to sum to zero, I multiplied each coefficient by its respective weight. When I used those adjusted coefficients in Proc Mixed, the contrasts are estimable. Is this the correct approach to fixing the error with the contrasts?

Thanks,
Mike Galyean