Modeling and Multivariate Methods - SAS

144 Fitting Stepwise Regression Models Chapter 4
Models with Crossed, Interaction, or Polynomial Terms
Table 4.5 Description of the Current Estimates Report (Continued)
SS
Reduction in the error (residual) sum of squares (SS) if the term is entered
into the model or the increase in the error SS if the term is removed from the
model. If a term is restricted in some fashion, it could have a reported SS of
zero.
“F Ratio” Traditional test statistic to test that the term effect is zero. It is the square of a
t-ratio. It is in quotation marks because it does not have an F-distribution for
testing the term because the model was selected as it was fit.
“Prob>F”
Significance level associated with the F statistic. Like the “F Ratio,” it is in
quotation marks because it is not to be trusted as a real significance
probability.
R Note: Appears only if you right-click in the report and select Columns > R.
Multiple correlation with the other effects in the model.
Step History Report
As each step is taken, the Step History report records the effect of adding a term to the model. For example,
the Step History report for the Fitness.jmp example shows the order in which the terms entered the model
and shows the statistics for each model. See “Example Using Stepwise Regression” on page 135.
Use the radio buttons on the right to choose a model.
Figure 4.8 Step History Report
Models with Crossed, Interaction, or Polynomial Terms
Often with models from experimental designs, you have cross-product or interaction terms. For continuous
factors, these are simple multiplications. For nominal and ordinal factors, the interactions are outer products
of many columns. When there are crossed terms, you usually want to impose rules on the model selection
process so that a crossed term cannot be entered unless all its subterms (terms that contain it) are in the
model.
Example Using Interaction Terms
1. Open the Reactor.jmp sample data table (Box, Hunter, and Hunter 1978).