Modeling and Multivariate Methods - SAS

Chapter 12 Fitting Dispersion Effects with the Loglinear Variance Model 311
Examining the Residuals
Table 12.2 Descriptions of Save Columns Options (Continued)
Std Error of Predicted
Std Error of Individual
Mean Confidence
Interval
Indiv Confidence
Interval
Creates a new column called Std Err Pred. The new column contains the
standard errors of the predicted values.
Creates a new column called Std Err Indiv. The new column contains the
standard errors of the individual predicted values.
Creates two new columns, Lower 95% Mean and Upper 95% Mean. The
new columns contain the bounds for a confidence interval for the prediction
mean.
Creates two new columns, Lower 95% Indiv and Upper 95% Indiv. The
new columns contain confidence limits for individual response values.
Row Diagnostics
Table 12.3 Descriptions of Row Diagnostics Options
Plot Actual by Predicted
Plot Studentized
Residual by Predicted
Plot Studentized
Residual by Row
Plots the observed values by the predicted values of Y. This is the leverage
plot for the whole model.
Plots the Studentized residuals by the predicted values of Y.
Plots the Studentized residuals by row.
Examining the Residuals
To see the dispersion effect, follow these steps:
1. Open the InjectionMolding.jmp sample data table.
2. Select Analyze > Fit Model.
Since the variables in the data table have preselected roles assigned to them, the launch window is
already filled out.
3. Click Run.
4. From the red triangle menu next to Loglinear Variance Fit, select Save Columns > Residuals.
5. In the InjectionMolding.jmp sample data table, right-click on the continuous icon next to Hold Time in
the Columns panel, and select Nominal.
6. Select Analyze > Fit Y by X.
7. Select Shrinkage Residual and click Y, Response.
8. Select Hold Time and click X, Factor.