Factor Analysis in SPSS
To conduct a Factor Analysis, start from the “Analyze” menu. This procedure is intended to reduce the complexity in a set of data, so we choose “Data Reduction” from the menu. And the choice in this category is “Factor,” for factor analysis.

This dataset gives children’s scores on subtests of the Wechsler Intelligence Scale for Children
(WISC-III). The Wechsler scales are scored to give you a “verbal” and a “performance” IQ.
The question is whether we can reproduce the verbal vs. nonverbal distinction, with the appropriate subtests grouping into each category, using factor analysis.

This dialog box will appear:
Factor analysis has no IVs and DVs, so everything you want to get factors for just goes into the list labeled “variables.” In this case, it’s all the variables. In some datasets, there is also a dummy “subject number” variable included. Be sure that you don’t include subject number as one of the variables for your factor analysis!

To do a factor analysis, we need to select an “extraction method” and a “rotation method.” Hit the “Extraction” button to specify your extraction method.

In this dialog box, you can make a number of selections. First, I want you to un-check the box labeled “Unrotated factor solution.” This is a default setting for your printout, but it just gives you information that you don’t need, and that may distract you from the real answers. So, always go into the Extraction sub-dialog and un-check this box.
Second, check the box for a “scree plot.” This will give you a scree diagram (as discussed in the lecture notes), which is one way to decide how many factors to extract.
Third, look at the section labeled “Extract.” As you can see, the default setting is for SPSS to use the Kaiser stopping criterion (i.e., all factors with eigenvalues greater than 1) to decide how many factors to