Modeling and Multivariate Methods - SAS

558 Visualizing, Optimizing, and Simulating Response Surfaces Chapter 24
The Profiler
Figure 24.3 Illustration of Traces
current predicted value
of response, changes by
dragging a factor value
current value of factor,
changes by dragging
the dotted line
95% confidence interval
on the mean response
current factor values
traces, lines, and error
bars show predicted
values
The Profiler in some situations computes confidence intervals for each profiled column. If you have saved
both a standard error formula and a prediction formula for the same column, the Profiler offers to use the
standard errors to produce the confidence intervals rather than profiling them as a separate column.
Interpreting the Profiles
The illustration in Figure 24.4 describes how to use the components of the Profiler. There are several
important points to note when interpreting a prediction profile:
• The importance of a factor can be assessed to some extent by the steepness of the prediction trace. If the
model has curvature terms (such as squared terms), then the traces may be curved.
• If you change a factor’s value, then its prediction trace is not affected, but the prediction traces of all the
other factors can change. The Y response line must cross the intersection points of the prediction traces
with their current value lines.
Note: If there are interaction effects or cross-product effects in the model, the prediction traces can shift
their slope and curvature as you change current values of other terms. That is what interaction is all about. If
there are no interaction effects, the traces only change in height, not slope or shape.