Issues in the detection and interpretation of interaction effects between quantitative variables in multiple regression analysis are discussed. Recent discussions associated with problems of multicollinearity are reviewed in the context of the conditional nature of multiple regression with product terms. (TJH)

A core assumption of the standard multiple regression model is independence of residuals, the violation of which results in biased standard errors and test statistics. The structural equation model (SEM) generalizes the regression model in several key ways, but the SEM also assumes independence of residuals. The multilevel model (MLM) was…

This paper shows that redundancy maximization with J. K. Johansson's extension can be accomplished via a simple iterative algorithm based on H. Wold's Partial Least Squares. The model and the iterative algorithm for the least squares approach to redundancy maximization are presented. (TJH)

Focuses on developing a systematic characterization of the error forms resulting from model misspecification in single equation models for least squares regression analyses. (Author/DEP)

Econometric techniques for estimating the parameters of individual and group multi-attribute utility models are discussed. These techniques permit measurement of intra-and inter-individual heterogeneity with regard to the importance ascribed to the model attributes. (Author/JKS)

Problems in testing main effects in regression analysis when there is interaction are discussed. A method by which main effects can be tested independently of the interaction is developed and compared with the hierarchical method. The method provides control of the type I error rate, but is quite conservative. (Author/JKS)

When either regression models or subjectively-weighted models are used as aids in making placement decisions, the discriminant validity of these models is questioned. The validity of several regression models and of subjectively weighted models was investigated in two experiments. (Author/JKS)

The study tests the appropriateness of multiplicative versus additive expectancy-valency models for grouping motivational force decisions of 82 undergraduate students. Arguments are offered favoring a non-nested regression models analysis over a traditional hierarchical analysis of nested regression models. Discriminant analysis indicated one of…

By using complex multiple regression models to generate regression surfaces, the relationships between academic achievement, creativity, and intelligence are examined. Findings indicate that for certain academic subjects creativity is related to achievement up to a threshold level of intelligence, but after the threshold has been reached…

Two major and two minor principles are shown to serve to generate a large number of multivariate models, including canonical analysis, factor analysis, and latent trait test theory. The statistical underpinnings of the theory are discussed. (Author/JKS)