Modeling and Multivariate Methods - SAS

Chapter 8 Analyzing Screening Designs 237
Additional Examples
Note asterisks mark four terms, indicating that they are not orthogonal to effects preceding them, and the
obtained contrast value was after orthogonalization. So, they would not match corresponding regression
estimates.
Analyzing a Supersaturated Design
Supersaturated designs have more factors than runs. The objective is to determine which effects are active.
They rely heavily on effect sparsity for their analysis, so the Screening platform is ideal for their analysis.
As an example, look at Supersaturated.jmp, from the Sample Data folder, a simulated data set with 18
factors but only 12 runs. Y is generated by
Y = 2( X7) + 5( X10) – 3( X15)
+ ε
where ε ~ N(0,1). So, Y has been constructed with three active factors.
To detect the active factors, run the Screening platform with X1–X18 as X and Y as Y. The report shown in
Figure 8.6 appears.
Figure 8.6 Screening Report for Supersaturated.jmp