THis is what is supposed to happen. In GLIMMIX (also MIXED, GLM, etc.) an overparameterized model is used.This is needed to properly test for factor effects and get expected values. With three factor levels, you need a model with three parameters, but the overparameterized model has four parameters (intercept, beta_A, beta_B, and beta_C). The last one ends up as 0 in the estimation. For one factor, this means that the intercept is the expected value for the last level (C), and the other parameters are differences from C. For instance, the expected value for A is intercept + beta_A. This is described in the User's Guide. ... View more