The OUTPUT statement creates a data set that contains predicted values and residual diagnostics, which are computed after
the model is fit. The variables in the input data set are *not* included in the output data set, in order to avoid data duplication for large data sets; however, variables that are specified
in the ID statement
are included. By default, only predicted values are included in the output data set.

If the input data are in distributed form, in which access of data in a particular order cannot be guaranteed, the HPLMIXED procedure copies the distribution or partition key to the output data set so that its contents can be joined with the input data.

For example, suppose that the data set `Scores`

contains the variables `Score`

, `Machine`

, and `Person`

. The following statements fit a model that has fixed machine and random person effects and save the predicted and residual
values to the data set `IgausOut`

:

proc hplmixed data = Scores; class machine person score; model score = machine; random person; output out=igausout pred=p resid=r; run;

You can specify the following syntax element in the OUTPUT statement: