Discriminant Function Analysis Results - Quick Tab
Select the Quick tab of the Discriminant Function Analysis Results dialog box to access the options described here. Use these options to quickly review summary statistics for the variables in the model and not in the model.
Summary: Variables in the model
Click the
Summary: Variables in the model button to produce a spreadsheet with summary statistics for all variables currently in the model:
Wilks' Lambda. The Wilks' Lambda for the overall model that will result after removing the respective variable. Remember that Wilks' Lambda can assume values in the range of 0 (perfect discrimination) to 1 (no discrimination).
Partial Lambda. The Wilks' Lambda associated with the unique contribution of the respective variable to the discriminatory power of the model.
F to remove
The
F-value associated with the respective partial Wilks'
Lambda.
p-value
The
p-value associated with the respective F to remove. Note that in stepwise analyses, these
p-values should be interpreted with caution; refer to the Overviews.
Tolerance
The tolerance value of a variable is computed as 1 - R-square of the respective variable with all other variables in the model (in this spreadsheet). Thus, the tolerance is a measure of the respective variable's redundancy. For example, a tolerance value of .10 means that the variable is 90% redundant with the other variables in the model.
1-Tolerance (R-square)
The R-square value of the respective variable with all other variables in the model (in this spreadsheet).
Variables not in the model
Click the
Variables not in the model button to produce a spreadsheet with the summary statistics for all variables that are currently not in the model. The statistics displayed in this spreadsheet are essentially identical to those described in
Variables in the model. Note that this option is only available if either the
Forward stepwise or
Backward stepwise method has been selected on the
Model Definition - Quick
tab.