# 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 SPSS® Statistics Standard Edition or the Advanced Statistics Option.

- From the menus choose:
- In the Predictors tab, select factors and covariates and then click Model.
- Select one or more factors or covariates or a combination of factors and covariates.
- Select a method for building the terms from the Type drop-down list and add them to the model.
- 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.

- 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.

## Specifying nested terms

- From the menus choose:
- On the Predictors tab, select factors and covariates and then click Model.
- Select a factor or covariate that is nested within another factor, and then click the move button.
- Under Build term, select the factor within which the previous factor or covariate is nested, and then click the move button.
- Click Add.
- Optionally, you can include interaction effects or add multiple levels of nesting to the nested term.

- Include intercept in model
- The intercept is usually included in the model. If you can assume the data pass through the
origin, you can exclude the intercept.
Models with the multinomial ordinal distribution do not have a single intercept term; instead there are threshold parameters that define transition points between adjacent categories. The thresholds are always included in the model.