Discriminant Function Analysis Results

Click the OK button in the Model Definition dialog box to display the Discriminant Function Analysis Results dialog box, which contains three tabs: Quick, Advanced, and Classification. Note that this dialog box will also be displayed if you click the OK button in the Discriminant Function Analysis Startup Panel if the Advanced Options check box on the

Discriminant Function Analysis

Startup Panel

- Quick

tab is cleared.

Summary box
The Summary box shows the Number of variables in the model, the Wilks' Lambda, the approximate F and the p-value.

Copy button. Click the Copy button to copy either the selected text (if text has been selected) in the Summary box or all of the text (if no text has been selected) to the Clipboard. Note that the copied text retains formatting information (such as font, color, etc.).

Contract/Expand button
Click the Contract/Expand button to contract or expand the Summary box. When contracted, you can see only one line of the Summary box text and can scroll through the text using the scroll bar. When contracted, the text is scrolled so that the first non-blank line is at the top. When expanded (the default setting), the entire Summary box will be displayed on the Discriminant Function AnalysisResults dialog.
Summary
Click the Summary 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 Wilk's 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).
Cancel
Click the Cancel button to close the dialog box and return to either the Model Definition dialog box or the Discriminant Function Analysis Startup Panel (depending on how the Discriminant Function Analysis Results dialog box was displayed).
Options
Click the Options button to display the Options menu.