JMP 12 Fitting Linear Models

Chapter 5 

Stepwise Regression Models

Find a Model Using Variable Selection

Stepwise regression is an approach to selecting a subset of effects for a regression model. It can be useful in the following situations:

• There is little theory to guide the selection of terms for a model.

• You want to interactively explore which predictors seem to provide a good fit.

• You want to improve a model’s prediction performance by reducing the variance caused by estimating unnecessary terms.

For categorical predictors, you can do the following:

• Choose from among various rules to determine how associated terms enter the model.

• Enforce effect heredity.

The Stepwise platform also enables you to explore all possible models and to conduct model ...