Day 10 - Team B - Aparna Vinod

Discriminant Analysis

What is Discriminant Analysis?

Discriminant analysis is a multivariate statistical method that serves to set up a model to predict group memberships. The model consists of discriminant functions that appear based on a linear combination of predictive variables that provide the best discrimination between groups. These functions are derived from a sample whose group memberships are known. Afterward, they could be applied to new individuals or units with measures related to the same variables and unknown group memberships. Although discriminant analysis is not frequently used in behavioral sciences because its assumptions are not always easy to meet, it is a conceptually and mathematically powerful multivariate statistical method. Therefore, a description and illustration of the discriminant analysis method may help increase its use.

What are the objectives of Discriminant Analysis?

Discriminant analysis can address any of the following research questions :

• Determining whether statistically significant differences exist between the average score profiles on a set of variables for two (or more) defined groups.
• Determining which of the independent variables account the most for the differences in the average score profiles of the two or more groups.
• Establishing procedures for classifying statistical units (individuals or objects) into groups on the basis of their scores on a set of independent variables.
• Establishing the number and composition of the dimensions of discrimination between groups formed from set of independent variables.

Discriminant Analysis in SPSS

You will now be taken through 

a discriminant analysis using data which includes demographic data and scores on 

various questionnaires. ‘smoke’ is a nominal variable indicating whether the employee 

smoked or not. The other variables to be used are age, days absent sick from work last year, 

self-concept score, anxiety score and attitudes to anti-smoking at work score. The aim of 

the analysis is to determine whether these variables will discriminate between those who 

smoke and those who do not. This is a simple discriminant analysis with only two groups 

in the DV. With three or more DV groupings a multiple discriminant analysis is involved, 

but this follows the same process in SPSS as described below except there will be more 

than one set of eigenvalues, Wilks’ Lambda’s and beta coefficients. The number of sets is 

always one less than the number of DV groups.

Step 1 : Open SPSS data file and go to Analyse >> Classify >> Discriminant

Step 2 : Select 'Smoke' as your grouping variable and enter it into the 'Grouping Variable Box'

Step 3 :  Click 'Define Range' button and enter the lowest and highest code for your groups (here it is 1 and 2) and click 'Continue'.

Step 4 : Select your predictors and enter into 'Independents Box' and select 'Enter Independents Together'. If you planned a step-wise analysis you would at this point select 'Use Stepwise Method' and not the previous instruction.

Step 5 :  Click on 'Statistics' button and select Means, Univariate Anovas, Box's M, Unstandardized and Within-Groups Correlation.

Step 6 : Go to Continue >> Classify and select Compute From Group Sizes, Summary Table, Leave One Out Classification, Within Groups and all Plots

Step 7 :  Go to Continue >> Save and select Predicted Group Membership and Discriminant Scores.

Step 8 : Click Ok.

The results are now ready for interpretation.