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Details of the FACTEX Procedure 
See FACTEX13 in the SAS/QC Sample Library 
Orthogonal factorial designs are most commonly used at the initial stages of experimentation. At these stages, it is best to experiment with as few levels of each factor as possible in order to minimize the number of runs required. Thus, these designs usually involve only two levels of each factor. Occasionally some factors will naturally have more than two levels of interest different types of seed, for instance.
You can create designs for factors with different numbers of levels simply by taking the cross product of component designs in which the factors all have the same numbers of levels, that is, replicating every run of one design for each run of the other. (See Example 15.14.) All estimable effects in each of the component designs, as well as all generalized interactions between estimable effects in different component designs, are estimable in the crossproduct; refer to Section 3 of Chakravarti (1956).
This example illustrates how you can construct a mixed level design using the OUTPUT statement with the POINTREP= option or the DESIGNREP= option to take the cross product between two designs.
Suppose you want to construct a mixedlevel factorial design for two twolevel factors (A and B) and one threelevel factor (C) with 12 runs. The following SAS statements produce a complete 3×2^{2} factorial design using design replication:
proc factex; factors a b; output out=ab; run; factors c / nlev=3; output out=drepdesn designrep=ab; run; proc print data=drepdesn; run;Output 15.7.1 lists the mixedlevel design saved in the data set DREPDESN. Output 15.7.1: 3×2^{2} MixedLevel Design Using Design Replication

proc factex; factors a b; output out=ab; run; factors c / nlev=3; output out=prepdesn pointrep=ab; run; proc print data=prepdesn; run;
Output 15.7.2 lists the mixedlevel design saved in the data set PREPDESN.
Output 15.7.2: 2^{2}×3 MixedLevel Design Using Point Replication

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