Related Procedures

Factor Analysis attempts to identify underlying variables that explain the pattern of correlations within a set of observed variables. This procedure is often used to reduce the number of variables in a data set but can also be used to explore the latent structure of the variables in your data file.

If you think the relationships between your variables are nonlinear, the Bivariate Correlations procedure offers correlation coefficients that are more appropriate for nonlinear associations.
If your analysis variables are not scale variables, you can try Hierarchical Cluster Analysis on the variables as an alternative to Factor Analysis for structure detection.