Modeling and Multivariate Methods - SAS

92 Fitting Standard Least Squares Models Chapter 3
Factor Profiling
In cases where the relative standard errors are different (perhaps due to unequal scaling), a similar report
appears. However, there is a different value for Lenth’s PSE for each estimate.
Description of Lenth’s Method
An estimate of standard error is calculated using the method of Lenth (1989) and shows in the Effect
Screening report (shown above). This estimate, called the pseudo standard error, is formed by taking 1.5
times the median absolute value of the estimates after removing all the estimates greater than 3.75 times the
median absolute estimate in the complete set of estimates.
Factor Profiling
Assuming that the prediction equation is estimated well, you still must explore the equation itself to answer
a number of questions:
• What type of curvature does the response surface have?
• What are the predicted values at the corners of the factor space?
• Would a transformation on the response produce a better fit?
The tools described in this section explore the prediction equation to answer these questions assuming that
the equation is correct enough to work with.
Profiler Shows prediction traces for each X variable. See “The Profiler” on page 93.
Interaction Plots
Contour Profiler
Mixture Profiler
Cube Plots
Box Cox Y
Transformation
Surface Profiler
Shows a matrix of interaction plots when there are interaction effects in the
model. See “Interaction Plots” on page 96.
Provides an interactive contour profiler, which is useful for optimizing
response surfaces graphically. See “Contour Profiler” on page 93.
Note: This option appears only if you specify the
Macros > Mixture Response Surface option for an effect.
Shows response contours of mixture experiment models on a ternary plot.
Select this option when three or more factors in the experiment are
components in a mixture. See “Mixture Profiler” on page 95.
Shows a set of predicted values for the extremes of the factor ranges. The
values are laid out on the vertices of cubes. See “Cube Plots” on page 97.
Finds a power transformation of the response that fits the best. See “Box Cox
Y Transformations” on page 98.
Shows a three-dimensional surface plot of the response surface. See “Surface
Profiler” on page 96.