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Chapter 9
NestedTerms
Youcan build nested terms for your model in this procedure. Nested terms are useful for modeling
the effect ofa factor or covariate whose values do not interact with the levels of another factor.
Fore xample, a grocerystore chain may follow the spending habits of its customers at several store
locations. Since each customer frequents only one of these locations, the Customer effect can be
said to be nested withinthe Store location effect.
Additionally,you can include interaction effects, such as polynomial terms involving the same
covariate, or add multiple levelsof nesting to the nested term.
Limitations. Nested terms have the following restrictions:
All factors withinan interaction must be unique. Thus, if Ais a factor, thenspecifying A*A
is invalid.
All factors withina nested effect must be unique. Thus, if Ais a factor,then specifying A(A)
is invalid.
No effect can be nested within a covariate. Thus, if Ais a factor and Xis a covariate, then
specifying A(X) is invalid.
Intercept. The intercept is usuallyi ncludedin the model. If you can assume the data pass through
the origin, you can exclude the intercept. Even if you include the intercept in the model, you
can choose to suppress statistics related to it.
Complex Samples General Linear Model Statistics
Figure 9-3
General Linear Model Statistics dialog box
ModelParame ters. This group allows you to control the display of statistics related to the model
parameters.
Estimate. Displays estimates of the coefficients.
Standarderror. Displays the standard error for each coefficient estimate.
Confidence interval. Displays a confidence interval for each coefficient estimate. The
confidence level for the interval is set in the Options dialog box.
Ttest.Displays a ttest of each coefficient estimate. The null hypothesis for each test is that
thevalueofthecoefficientis 0.