Generalized Linear Models Model

Specify Model Effects
The default model is intercept-only, so you must explicitly specify other model effects. Alternatively, you can build nested or non-nested terms.

Non-nested terms

For the selected factors and covariates:

Main effects
Creates a main-effects term for each variable selected.
Interaction
Creates the highest-level interaction term for all selected variables.
Factorial
Creates all possible interactions and main effects of the selected variables.
All 2-way
Creates all possible two-way interactions of the selected variables.
All 3-way
Creates all possible three-way interactions of the selected variables.
All 4-way
Creates all possible four-way interactions of the selected variables.
All 5-way
Creates all possible five-way interactions of the selected variables.

Specifying non-nested terms

This feature requires Custom Tables and Advanced Statistics.

Analyze > Generalized Linear Models > Generalized Linear Models

2. In the Predictors tab, select factors and covariates and then click Model.
3. Select one or more factors or covariates or a combination of factors and covariates.
4. Select a method for building the terms from the Type drop-down list and add them to the model.
5. Repeat the process until you have all of the terms that you want in the model.

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 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 within the Store location effect.

Additionally, you can include interaction effects, such as 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.