Note: See Mixed-Level Designs Using Pseudo-Factors in the SAS/QC Sample Library.
If the numbers of levels for the factors of the mixed-level design are all powers of the same prime power q, you can construct the design by using pseudo-factors, where the levels of k q-level pseudo-factors are associated with the levels of a single derived factor with levels. Refer to Section 5 of Chakravarti (1956) and see the section Types of Factors for details.
For example, the following statements create a design for one 4-level factor (A
) and three 2-level factors (B, C
, and D
) in 16 runs (a half replicate):
proc factex; factors A1 A2 B C D; model estimate =(B C D A1|A2 ) nonnegligible=(B|C|D@2 A1|A2|B A1|A2|C A1|A2|D); size design=16; output out=DesignA [A1 A2]=A cvals = ('A' 'B' 'C' 'D'); run; proc print; var A B C D; run;
The levels of two 2-level pseudo-factors (A1
and A2
) are used to represent the four levels of A
. Hence the three degrees of freedom associated with A
are given by the main effects of A1
and A2
and their interaction A1
*A2
, and you can thus refer to (A1
|A2
) as the main effect of A
.
The MODEL statement specifies that the main effects of all factors are to be estimable, and that all of the two-factor interactions
between B, C
, and D
, in addition to the interactions between each of these and (A1
|A2
), are to be nonnegligible. As a result, the mixed-level design has resolution 4. The design is saved in the data set DesignA
, combining the levels of the two pseudo-factors, A1
and A2
, to obtain the levels of the 4-level factor A
. The data set DesignA
is listed in Output 7.8.1.
Output 7.8.1: Design of Resolution 4 in 16 Runs