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

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

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

Obtaining a generalized linear mixed model