A Fortran IV computer program is presented which will unambiguously partition the explained variance of a dependent variable into those parts due uniquely to each independent variable and to all possible combinations of independent variables through commonality analysis. Tests of significance and documentation are provided. (Author/JKS)

The multitude of procedures for testing hypotheses about mean contrasts often presented in statistical methods textbooks is unwarranted. This article demonstrates that nearly all such research can be handled by a single contrast test statistic often attributed to R. A. Fisher. (TJH)

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…

Three traditional methods of selection of variables to be included in a "best" regression equation are compared to a method designed to maximize weight validity. Implications for constructing regression equations for prediction are discussed, with consideration of the weight validity maximization method recommended in crucial situations.…

Several advantages to the use of different kinds of factor scores as independent variables in a multiple regression equation are reported. A computer program is presented which will calculate a regression equation using a variety of factor scores. (Author/JKS)

This study compared double cross-validation replication predictive accuracies of six types of factor scores with full-rank data by utilizing data in which classroom achievement was predicted from affective and cognitive variables. Prediction was significantly more accurate for factor scores than for full-rank data. (Author/CP)

An empirical method called Predicted Error Sum of Squares (PRESS) is advanced and studied. This method is used to examine the cross-validated prediction accuracies of some popular algorithms for weighted predictor variables. The weighting methods that were considered were ordinary least squares, ridge regression, regression on principal…

Several advantages to the use of factor scores as independent variables in a multiple regression equation were found. To help select the most desirable type of factor score on which to calculate a regression equation, computer-based Monte Carlo methods were used to compare the predictive accuracy upon replication of regression of five…

Common factor scores were compared to unfactored data-level variables as predictors in terms of the correlation of a criterion with the predicted value in multiple regression equations applied to replication (cross-validation) samples. (Editor)

Computer-based Monte Carlo methods compared the predictive accuracy upon replication of regression of five complete and four incomplete factor score estimation methods. Prediction on incomplete factor scores showed better double cross-validated prediction accuracy than on complete scores. The unique unit-weighted factor score was superior among…

A multiple regression analysis of the relationship between prospective teachers' scientific understanding and Gender, Education Level (High School, College), Courses in Science (Biology, Chemistry, Physics, Earth Science, Astronomy, and Agriculture), Attitude Towards Science, and Attitude Towards Mathematics is reported. Undergraduate elementary…