Specify a hierarchical model for Fit Regression Model and Linear Regression

Stat > Regression > Regression > Fit Regression Model > Model > Specify a Non-Hierarchical Model > Hierarchy, select OK

Predictive Analytics Module > Linear Regression > Model > Specify a Non-Hierarchical Model > Hierarchy, select OK

Use to allow Minitab to add the displayed terms to the model in order to create a hierarchical model. In a hierarchical model, all lower-order terms that comprise the higher-order terms also appear in the model. For example, a model that includes the interaction term A*B*C must also include the terms: A, B, C, A*B, A*C, and B*C to be hierarchical.

Models can be non-hierarchical. Generally, you can remove lower order terms if they are insignificant, unless subject area knowledge suggests that you include them. Models that contain too many terms can be relatively imprecise and can reduce the ability to predict the values of new observations.

Consider the following tips:

Fit a hierarchical model first. You can remove insignificant terms later.
If you standardize your predictors, fit a hierarchical model to produce an equation in uncoded (or natural) units.
If your model contains categorical variables, the results are easier to interpret if the categorical terms, at least, are hierarchical.

Would you like Minitab to make your model hierarchical?

Specify whether Minitab adds terms to the model.

Add terms to make the model hierarchical (recommended): Minitab will add the displayed terms to produce a hierarchical model.
Use the specified non-hierarchical model: Minitab will not add the terms.

Use this choice from now on (Fit Regression Model for the desktop app)

Select to make your choice the default. You will skip this dialog in the future. If you check this option, you can change the setting in File > Options > Linear Models > Model Hierarchy.