Abstract
This paper introduces new predictive measures of association that may be used for contingency table analysis much as the simple, partial, and multiple correlation coefficients are used for regression analysis. The new measures are based on the combination of (1) the logic of the PRE (proportional reduction in error) measures of association, (2) the use of uncertainty (or maximum-likelihood-ϰ2) as indirect measures of errors in prediction, and (3) analysis strategy of log-linear models for contingency tables.