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The FACTEX Procedure |
Table 7.5 summarizes basic design types that you can construct with the FACTEX procedure by providing example code for each type.
Design Type |
Example Statements |
---|---|
A full factorial design in three factors, each at two levels coded as |
proc factex; factors Pressure Temperature Time; examine design; run; |
A full factorial design in three factors, each at three levels coded as |
proc factex; factors Pressure Temperature Time / nlev= 3; examine design; run; |
A full factorial design in three factors, each at two levels. The entire design is replicated twice, and the design with recoded factor levels is saved in a SAS data set. |
proc factex; factors Pressure Temperature Time; output out= SavedDesign designrep= 2 Pressure cvals=('low' 'high') Temperature nvals=(200 300) Time nvals=(10 20); run; |
A full factorial design in three factors, each at two levels coded as |
proc factex; factors Pressure Temperature Time; output out= SavedDesign pointrep= 3 randomize; run; |
A full factorial design in three control factors, each at two levels coded as |
proc factex; factors+ Pressure Temperature Time; output out =+ SavedDesign pointrep=+ OutArray; run; |
A full factorial blocked design in three factors, each at two levels coded as |
proc factex; factors Pressure Temperature Time; blocks nblocks= 2; output out= SavedDesign; run; |
A full factorial blocked design in three factors, each at two levels coded as |
proc factex; factors Pressure Temperature Time; blocks size= 4; output out= SavedDesign blockname= Machine cvals=('A' 'B' ); run; |
A fractional factorial design of resolution 4 in four factors, each at two levels coded as |
proc factex; factors Pressure Temperature Time Catalyst; size design= 8; model resolution= 4; examine design; run; |
A one-half fraction of a factorial design in four factors, each at two levels coded as |
proc factex; factors Pressure Temperature Time Catalyst; size fraction= 2; model resolution=maximum; examine design aliasing confounding; run; |
A one-quarter fraction of a factorial design in six factors, each at two levels coded as |
proc factex; factors x1-x6; size fraction= 4; model estimate=( x1 x2 x3 x4 x5 x6 ) nonneg =( x1*x5 x1*x6 x5*x6 ); output out = SavedDesign; run; |
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