MODEL
effects </ options> ;
You use the MODEL statement to specify the independent effects used to model data that are to be collected with the design that is being constructed. The effects can be
simple continuous regressor effects
polynomial continuous effects
main effects of classification variables
interactions of classification variables
continuous-by-class effects
The variables used to form effects in the MODEL statement must be present in all input data sets. For details on input data sets, see the section Input Data Sets. For details on the specification of different types of effects and on how the design matrix is defined with respect to the effects, see the section Specifying Effects in MODEL Statements.
If you specify a data set containing fixed covariate effects with a DESIGN= data set in the BLOCKS statement, then a CLASS or MODEL statement that follows the BLOCKS statement refers to the model for the fixed covariates. A CLASS or MODEL statement that defines the model for the candidate points (treatment model) should occur before the BLOCKS statement.
The following options can be used in the MODEL statement: