In most research, linear regression analyses are performed without taking into account published results (i.e., reported summary statistics) of similar previous studies. Although the prior density in Bayesian linear regression could accommodate such prior knowledge, formal models for doing so are absent from the literature. The goal of this…

Due to its extensive applicability and computational ease, moderated multiple regression (MMR) has been widely employed to analyze interaction effects between 2 continuous predictor variables. Accordingly, considerable attention has been drawn toward the supposed multicollinearity problem between predictor variables and their cross-product term.…

This is an application of contemporary multilevel regression modeling to the prediction of academic performances of 1st-year college students. At a first level of analysis, the data come from N greater than 16,000 students who were college freshman in 1994-1995 and who were also participants in high-level college athletics. At a second level of…

Person fit is the degree to which an item response model fits for individual examinees. Reise (2000) described how two-level logistic regression can be used to detect heterogeneity in person fit, evaluate potential predictors of person fit heterogeneity, and identify potentially aberrant individuals. The method has apparently never been applied to…

The cross-validated classification accuracies of three predictor weighting strategies (least squares, ridge regression, and reduced rank) were compared under varying simulated data conditions for the two-group classification problem. Results were somewhat similar to previous findings with multiple regression when absolute rather than relative…

Set correlation is a multivariate generalization of multiple regression/correlation analysis that features the employment of overall measures of association interpretable as proportions of variance and the use of set-partialled sets of variables. The statistical development of the theory and several examples are presented. (Author/JKS)

Methods for comparing the suitability of alternative models for covariance matrices are examined. A cross-validation procedure is suggested and its properties examined. A series of examples using longitudinal data are examined. (Author/JKS)

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)

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)

The misleading character of the correlation coefficient was investigated in two studies of intuitive statistical behavior: subjective estimation of partial correlation and subjective estimation of the minimum possible correlation between two variables given their equal correlation with a third. (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…