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In the multiple-way analysis of variance we explain the variation
of a dependent variable by two ore more variables with nominal scale,
i.e. by grouping variables. The grouping variables are given by the
GROUPING parameter followed by the definition of their grouping
structure (not obligatory).

The main effects and interactions of the grouping variables to be
included in the model are defined by the INCLUDED and/or EXCLUDED
parameters. The grouping variables are referenced by their initials,
which should be unique. The default model is always the model with all
possible interactions.
The following example defines a three-way fixed effects analysis of
variance model with three main effects and interaction AS:

   ANOVA IEADATA,20
   DEPENDENT=KNOWLDGE
   GROUPING=ATTITUDE,SEX,GRADE
   ATTITUDE=1,2,3  SEX=1,2  GRADE=1,2,3
   INCLUDED=AS,G

Further information:
   1 = More on definitions for grouping variables 
   2 = More on main effects and interactions to be included in the model 
   3 = Different methods of forming hypotheses 
   4 = Error terms transformed or assigned by the user 
   R = Random effects and mixed models 
   E = Estimates of the effects, computing residual and predicted values 
   A = More on ANOVA operations