This example illustrates the best-subset regression facilities of GRM,
and how they can be applied to experimental designs. The FORCE
keyword is used to force all five main effects into the model; GRM
will then search for a best subset of up to 5 additional two-way interactions
(i.e., START = 6, STOP
= 10). A unique feature of GRM
is that when categorical predictor variables or effects have more than
a single degree of freedom (as in this example), the stepwise and best-subset
procedures ensure that the coded (sigma-restricted) variables representing
the categorical predictors are moved in or out of the model as a block
(so that always complete multi-degree of freedom effects are included
or excluded from the final model). You can run the example shown below
using the example data file

GRM;

{ Dependent variable (list): }

{ Specification of grouping variables (factors); note that

{ Here the bar operator and the @ operator are used to construct the

{ Best-subset regression is requested as the model building method. }

{ Here the first 5 effects, i.e., main effects, are "forced" into the model. }

{ Mallow's Cp index is will be used to evaluated the subsets. }

{ The search for the subsets will begin with subsets of size 6, up to

For more examples, see GRM Syntax - Examples.