Working with the Fit Summary Window

The Fit Summary plots the relative importance of each variable as measured by its p-value. The p-value is plotted on a log scale and the alpha value (plotted as -log(alpha)), is shown as a vertical line. To adjust the alpha value, click, drag, and drop the vertical line. A histogram of the p-values is displayed at the bottom of the window.

The Variable Importance plot enables you to select a single variable to inspect within each level of the group by variable. Use the drop-down menu to select which variable you want to inspect. Each dot in the Variable Importance plot represents a model effect. The bars are drawn for the effect selected in the drop-down menu.

The Goodness of Fit plot, which is not available when there is no group by variable, displays how well the model predicts the response variable within each level of the group by variable. Use this plot to determine whether your model has a significantly different fit within different levels.

Notice that when you select a group by variable, the Residual Plot, Assessment, and Influence Plot are updated. These plots enable you to further inspect the variable within each level of the group by variable.

Use to specify how the plots are sorted.