You are getting the default choices for predicted values and residuals. These are considered conditional values (conditional on the random effects). Thus, you are getting the predicted value (predicted linear predictor) for {x1,x2,x3} for each hosp value in the data set. These are considered BLUPs (actually, EBLUPs). Even if the independent variables were the same, the predicted value would be different for two different hosp values. The residual is just the difference with the observed (calculated on the link scale). If you want the so-called marginal predictions (i.e., at the expected value of 0 for the random hosp effect), use: output out=gmxout2 pred(noblup)=pred residual(noblup)=residual; Check out the following for more guidance, or the User's Guide. http://www2.sas.com/proceedings/sugi30/196-30.pdf
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