# Add a Custom Term (generalized linear mixed models)

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.

Constructing a nested term

- Select a factor or covariate that is nested within another factor, and then click the arrow button.
- Click (Within).
- Select the factor within which the previous factor or covariate is nested, and then click the arrow button.
- Click Add Term.

Optionally, you can include interaction effects or add multiple levels of nesting to the nested term.