GRM Syntax -
Example 2: Stepwise Multiple Regression with Categorical Predictors
This example illustrates the specification for a stepwise multiple regression
problem with a single dependent variable and categorical predictors. When
categorical predictor variables or effects have more than a single degree
of freedom, the stepwise and best-subset procedures in STATISTICA
GRM
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).
Note that brief descriptive comments are enclosed in curly brackets.
You can run this example with the example data file Exp.sta.
GSR;
{ Dependent variable (list): }
DEPENDENT
= STRESS_R;
{ Specification of grouping variables (factors);
note that
optional grouping
codes (values) are specified to identify
the (selected)
groups in the categorical predictors. }
GROUPS
= GENDER ("MALE" "FEMALE")
TIME
(1 2 3);
{ Specification of continuous predictor variables
(covariates) }
COVARIATE
= CORRECT1 CORRECT2 CORRECT3;
{ Here the bar operator is used to construct
the full factorial
design for the
categorical predictor variables; the bar operator
will evaluate
to all main effects and interactions
between the grouping
variables. }
DESIGN
= CORRECT1+CORRECT2+CORRECT3
+
GENDER
| TIME;
{ Forward stepwise regression is requested
as the model building
method. }
MBUILD
= FSTEPWISE;
{ The maximum number of steps is 10. }
MAXSTEP
= 10;
{ p
to enter is 0.10. }
P1ENTER
= .10;
{ p
to remove is 0.10. }
P2REMOVE
= .10;
For more examples, see GRM Syntax -
Examples.