Discriminant Analysis with SPSS

Discriminant Analysis with SPSS

Rather than working with pre-existing classifications of subjects, as the other tests in 
Chapter 9 do, a discriminant analysis attempts to create classifications. To conduct a 
discriminant analysis in SPSS, therefore, you cannot use the "General Linear Model" 
function. The following process allows you to use continuous values to predict subjects' 
group placements.
1. Choose the "Classify" option in SPSS Analyze pull-down menu. 
2. Identify your desired type of classification as "Discriminant." Choose "Discriminant" 
from the prompts given. A window entitled a window entitled Discriminant Analysis
should appear. 
FIGURE 9.9 –SPSS DISCRIMINANT ANALYSIS WINDOW
The user identifies the variables involved in a one-way discriminant analysis by selecting their names from 
those listed on the left side of the Discriminant Analysis window. SPSS performs the test using variables with 
names placed into the "Independents" and variables with names placed into the "Grouping Variables" box.The user identifies the variables involved in a one-way discriminant analysis by selecting their names from 
those listed on the left side of the Discriminant Analysis window. SPSS performs the test using variables with 
names placed into the "Independents" and variables with names placed into the "Grouping Variables" box.
3. In this window, you can define the variables involved in the analysis as follows
a. Move the name of the categorical dependent variable from the box on the left to the 
"Grouping Variable" box. You must also click on the "Define Range" button below 
this box and type the values for the lowest and highest dummy-variable values used 
to identify groups. 
b. Identify the continuous measure(s) used to predict subjects' categories by moving 
the names of the predictor(s) to the "Independents" box. 
4. Click OK.
The Discriminant Analysis' "Independents Variable" box allows you to identify more than 
one predictor of subjects' categories. Inputting more than one independent variable leads 
to a multiple discriminant analysis. The analysis presented in Chapter 9's examples, though, 
use a single independent variable.

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