Screening experiments are aimed at identifying the factors that affect a response. Because identification of important factors is the goal (rather than sophisticated modeling), continuous factors in a screening design are typically set at only two levels. However, a screening situation might also involve discrete numeric or categorical factors, in which case classical screening designs might not fit your situation. You might also be interested in screening continuous factors with three levels. The Screening Design platform can handle multiple types of factors: continuous factors, categorical factors, and discrete numeric factors.
The Screening Design platform can accommodate the following three groups of screening designs:
• Classical designs: For situations where standard screening designs exist, you can choose from a list that includes factorial, Plackett-Burman, Cotter, and mixed-level designs. See Fractional Factorial Designs.
• Main effects screening designs: When desired or when a standard design is not available, you can construct a main effects screening design. These designs are orthogonal or near orthogonal and focus on estimating main effects in the presence of negligible interactions. See Main Effects Screening Designs.
• Mixed-level screening designs: When you have at least four continuous factors or three-level discrete numeric factors, you can construct a mixed-level design. These designs use continuous factors at three-levels. They are orthogonal, or near orthogonal, for main effects with minimal confounding between main effects and two-factor interactions. See Mixed-Level Screening Designs.