Modeling and Multivariate Methods - SAS

84 Fitting Standard Least Squares Models Chapter 3
Effect Screening
Normal Plot
The final Effect Screening options provide more reports:
• The Effect Screening report contains the Lenth PSE (pseudo-standard error) value.
• The Parameter Estimate Population report highlights significant factors.
You can also look at the model parameters from different angles using scaled estimates and three plots. See
“Parameter Estimate Population Report” on page 88 for details.
The Normal Plot option displays a Parameter Estimate Population report (see “Parameter Estimate
Population Report” on page 88) and shows a normal plot of these parameter estimates (Daniel 1959). The
estimates are on the vertical axis, and the normal quantiles on the horizontal axis.
Example of a Normal Plot
1. Open the Reactor.jmp sample data table.
2. Select Analyze > Fit Model.
3. Select Y and click Y.
4. Make sure that the Degree box has a 2 in it.
5. Select F, Ct, A, T, and Cn and click Macros > Factorial to Degree.
6. Click Run.
7. From the red triangle menu next to Response Y, select Effect Screening > Normal Plot.
Figure 3.22 Normal Plot
If all effects are due to random noise, they tend to follow a straight line with slope σ, the standard error. In
the plot, the line with slope equal to the Lenth’s PSE estimate is blue.
The Normal plot helps you identify effects that deviate from the normal lines. Estimates that deviate
substantially are labeled.