Analyzing Marketing Research Data with Association Models

Abstract

The author demonstrates the usefulness of some association models for ordered cross-classifications. The models are applied to problems common in marketing research, including analyzing the association in tables, determining criteria for collapsing categories in tables, assigning category scores to cross-classified ordered variables, and deriving correlation coefficient estimates for cross-classifications. These methods are shown to be particularly useful when the variables are partially ordered, for example in cases in which the variables contain “don't know” responses.