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1.
Select Help > Sample Data Library and open Reactor.jmp.
2.
Select Analyze > Fit Model.
3.
Select Y and click Y.
4.
Make sure that 2 appears in the Degree box near the bottom of the window.
5.
Select F, Ct, A, T, and Cn and click Macros > Factorial to Degree.
6.
Click Run.
7.
Select Estimates > Sorted Estimates from the red triangle menu.
Figure 3.21 Sorted Parameter Estimates
The effects are sorted by the absolute value of the t ratio, showing the most significant effects at the top.
A bar chart shows the t ratio with vertical lines showing critical values for the 0.05 significance level.
Screening experiments often involve fully saturated models, where there are not enough degrees of freedom to estimate error. In these cases, the Sorted Estimates report (Figure 3.21) gives relative standard errors and constructs t ratios and p-values using Lenth’s pseudo standard error (PSE). These quantities are labeled with Pseudo in their names. See Lenth’s PSE and Pseudo t-Ratios. A note explains the change and shows the PSE.
A t ratio for the estimate, computed using pseudo standard error. The value of Lenth PSE is shown in a note at the bottom of the report.
A p-value computed using an error degrees of freedom value (DFE) of m/3, where m is the number of parameters other than the intercept. The value of DFE is shown in a note at the bottom of the report.
Lenth’s pseudo standard error (PSE) is an estimate of residual error due to Lenth (1989). It is based on the principle of effect sparsity: in a screening experiment, relatively few effects are active. The inactive effects represent random noise and form the basis for Lenth’s estimate.
1.
Select Help > Sample Data Library and open Reactor.jmp.
2.
Select Analyze > Fit Model.
3.
Select Y and click Y.
4.
5.
Click the Macros button and select Full Factorial.
6.
Click Run.
Figure 3.22 Sorted Parameter Estimates Report for Saturated Model

Help created on 3/19/2020