SAS Institute. The Power to Know

Getting Started with the SAS(R) 9.2 ADX Interface for Design of Experiments

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Full Factorial Designs

Points to Remember

  • You can create different folders for organizing your designs in ADX.
  • Once responses are entered into a design, the design is frozen and can no longer be changed.
  • ADX uses coded values (-1 for low and 1 for high) for factors when fitting.
  • The Explore Data window provides a variety of graphical displays for examining the structure of your data prior to model fitting.
  • Main-effects plots provide a way to look at the effects of individual factors on the response.
  • Interaction plots indicate the presence and strength of two-factor interactions.
  • The Zoom feature provides more detail for individual cells within the interaction matrix.
  • Factorial plots help you to visualize the factorial structure in tree form.
  • The Effect Selection window provides a wealth of methods for automatically selecting significant effects in a fitted master model.
  • ADX uses ANOVA as the automatic effect selection method for a full factorial model with degrees of freedom for estimating error. ADX uses Lenth's method for saturated factorial designs.
  • The Effect Selection window offers a variety of graphical methods for displaying significant effects, including normal and Pareto plots.
  • ADX follows the principle of model hierarchy for building the predictive model. You can override this principle.
  • The Prediction Profiler is an interactive tool for exploring the effect of changing factor settings on predicted values.
  • You can augment the Prediction Profiler with desirability functions that you can use to find those factor settings that maximize the overall desirability.