Why Use Optimal Scaling?

Categorical data are often found in marketing research, survey research, and research in the social and behavioral sciences. In fact, many researchers deal almost exclusively with categorical data.

While adaptations of most standard models exist specifically to analyze categorical data, they often do not perform well for datasets that feature:

• Too few observations
• Too many variables
• Too many values per variable

By quantifying categories, optimal scaling techniques avoid problems in these situations. Moreover, they are useful even when specialized techniques are appropriate.

Rather than interpreting parameter estimates, the interpretation of optimal scaling output is often based on graphical displays. Optimal scaling techniques offer excellent exploratory analyses, which complement other IBM® SPSS® Statistics models well. By narrowing the focus of your investigation, visualizing your data through optimal scaling can form the basis of an analysis that centers on interpretation of model parameters.