Working with the Fit Summary Window

The Fit Summary window 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.

When your analysis includes a group by variable, the Fit Summary window displays a Goodness of Fit plot and Variable Importance plot.

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 the variable that you want to inspect. Each dot in the Variable Importance plot represents a model effect. The bars are for the model effect chosen 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 level, the Residual Plot, Assessment, and Influence Plot windows are updated. This enables you to further investigate each level of the group by variable.

Use the icon to specify how the plot is sorted.