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Chapter 9
Nested Terms
You can build nested terms for your model in this procedure. Nested terms are useful for modeling
the effect of a factor or covariate whose values do not interact with the levels of another factor.
For example, a grocery store chai
n 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 within the Store location effect.
Additionally, you can include in
teraction effects, such a s polynomial terms involving the same
covariate, or add multiple levels of nesting to the nested term.
Limitations. Nested terms have the following restrictions:
All factors within an interaction must be unique. Thus, if A is a factor, then specifying A*A
is invalid.
All factors within a nested effect must be unique. Thus, if A is a factor, then specifying A(A)
is invalid.
No effect can be nested within a covariate. Thus, if A is a factor and X is a covariate, then
specifying A(X) is invalid.
Intercept. The intercept is usually included in 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
Model Parameters. This group allows you to control the display of statistics related to the model
parameters.
Estimate. Displays estimates of the coefficients.
Standard error. Displays the standard error for each coefficient e stimate
.
Confidence interval. Displays a confidence interval for each coefficient e
stimate. The
confidence level for the interval is set in the Options dialog box.
Ttest. Displays a t test of each coefficient estimate. The null hypothesis for each test is that
thevalueofthecoefficient is 0.