If your general linear model includes nested factors or random factors, or if it uses binary coding, the following are restrictions on the procedures that you can perform.
- If your model contains random factors, you must
specify a hierarchical model in the
procedures are not available for models that contain random
Comparisons are not available for terms that contain or interact with random
factors. Nesting is a form of interaction. Suppose the model
contains A B C A*B, where both A and C are random, and B is fixed.
Because A*B is a term in the model, no multiple comparison results
for B are available even though B is a fixed factor. However, if
the model does not include A*B, multiple comparison results are
available for B.
There is a special case for a balanced design that has two
factors. Suppose the model contains A B A*B, where A is random, and
B is fixed. Even though A*B is in the model, you can perform
multiple comparisons for B.
- Comparisons is disabled if you choose
coding and the model is non-hierarchical. To enable
for this case, choose
(-1, 0, +1)
coding or specify a hierarchical model.
- Factorial Plots cannot display nested factors.
- Predict cannot calculate confidence intervals when the model contains
- Predict is not available for models that contain nested factors.
- Response Optimizer is not available for models that contain nested factors.