A general model for prediction and association is described for the situation in which both criterion and predictor(s) are discrete variables. The approach can be employed for the general case involving any number of predictors, and the related measures of multiple and partial association are described. (Author/GK)

A definition of a suppressor variable is presented which is based on the relation of the semipartial correlation to the zero order correlation. Advantages of the definition are given. (Author/JKS)

Effects of overextracting factors and components within and between maximum likelihood factor analysis and principal components analysis were examined through computer simulation of a range of factor and component patterns. Results demonstrate similarity of component and factor scores during overextraction. Overall, results indicate that…

Principal component, image component, three types of factor score estimates, and one scale score method were compared over different levels of variables, saturations, sample sizes, variable to component ratios, and pattern rotations. There were virtually no overall differences among methods, with the average correlation between matched scores…