Definitive Screening Design for Eight Continuous Factors shows an example of a definitive design with eight continuous factors. and four Extra Runs that correspond to fake factors. Notice the following:
Definitive Screening Design for Eight Continuous Factors
Definitive screening designs in JMP are constructed using conference matrices (Xiao et al., 2012). A conference matrix is an m x m matrix C where m is even. The matrix C has 0s on the diagonal, off-diagonal entries equal to 1 or –1, and satisfies .
Note: For certain even values of m, it is not known if a conference matrix exists.
Suppose that the number of factors, k, is five or larger. For the case of k ≤ 4 factors, see Definitive Screening Designs for Four or Fewer Factors.
Consider the case of k continuous factors and suppose that a conference matrix is available.
When k is even, the k x k conference matrix is used to define k runs of the design. Its negative, –C, defines the foldover runs. A center point is added to the design to ensure that a model containing an intercept, main effects, and quadratic effects is estimable. So, for k even, the minimum number of runs in the definitive screening design is 2k + 1.
When k is odd, a (k+1) x (k+1) conference matrix is used, with its last column deleted. A center point is added. Thus, for k odd, the minimum number of runs in the screening design is 2k + 3.
When there are k factors and k is even, the number of runs in the design is 2k + 2.
When k is odd, the number of runs is 2k + 4.
For those values of m for which a conference matrix is not available, a definitive screening design can be constructed using the next largest conference matrix. As a result, the required number of runs might exceed 2k + 3, in the continuous case, and 2k + 4, in the categorical case.
Extra runs are constructed using fictitious, or fake, factors. Adding k1 fake factors to a design results in 2k1 additional runs.
Denote the number of factors in your experimental study by k. Extra runs are constructed by creating a design for k + k1 factors, as described in Conference Matrices and the Number of Runs, and then dropping the last k1 columns. If k1 = 2, four extra runs are added. If k1 = 3, eight extra runs are added. As few as four extra runs can be highly beneficial in model selection.
Definitive screening designs for four or fewer factors are constructed using the five-factor definitive screening design as a base. This is because designs for k ≤ 4 factors constructed strictly according to the conference matrix approach have undesirable properties. In particular, it is difficult to separate second-order effects.
If you specify k ≤ 4 factors, a definitive screening design for five factors is constructed and unnecessary columns are dropped. For this reason, the number of runs for an unblocked design with k ≤ 4 factors is 13 if all factors are continuous or 14 if some factors are categorical.

Help created on 9/19/2017