A certain class of patterns of association can be investigated by fitting multiplicative models to a contingency table or by using covariance selection on a covariance matrix. Each multiplicative model for a contingency table corresponds to one particular covariance selection model, and the resulting similarities in the interpretation of patterns are emphasized in test statistics for each pattern and in implied marginal associations among variable pairs. [Examples on blood circulation change, prenatal malformations, personality traits and disease symptoms are briefly mentioned.].