Dominance analysis (DA) is a very useful tool for ordering independent variables in a regression model based on their relative importance in explaining variance in the dependent variable. This approach, which was originally described by Budescu, has recently been extended to use with structural equation models examining relationships among latent…

This study discusses quantile regression methodology and its usefulness in education and social science research. First, quantile regression is defined and its advantages vis-à-vis vis ordinary least squares regression are illustrated. Second, specific comparisons are made between ordinary least squares and quantile regression methods. Third, the…

Spline (or piecewise) regression models have been used in the past to account for patterns in observed data that exhibit distinct phases. The changepoint or knot marking the shift from one phase to the other, in many applications, is an unknown parameter to be estimated. As an extension of this framework, this research considers modeling the…

An empirical method (PRESS) for examining and contrasting the cross-validated prediction accuracies of some popular algorithms for weighting predictor variables was advanced and examined. The sample specific PRESS method was suggested as most appropriate when selecting among several alternative weighting algorithms to achieve maximum…

A method requiring minimal computational effort is presented for transforming ordered residuals for purposes of testing the correctness of a regression model. The method maintains the same logical ordering in the transformed residuals as that of the original residuals and is suitable for either correlated or uncorrelated data. (Author/BS)

The concept of change is related to suppressor variable conditions in a least square regression model. The domain of conditions necessary for a weighted change score composite to emerge as an underlying construct is mapped and the information loss through arbitrary assignment of weights to a change composite is explored. (Author/BW)

Although methods for using ordinary least squares regression computer programs to calculate a ridge regression are available, the calculation of a stepwise ridge regression requires a special purpose algorithm and computer program. The correct stepwise ridge regression procedure is given, and a parallel FORTRAN computer program is described.…

Ridge regression offers advantages over ordinary least squares estimation when a validity shrinkage criterion is considered. Comparisons of cross-validated multiple correlations indicate that ridge estimation is superior when the predictors are multicollinear, the number of predictors is large relative to sample size, and the population multiple…

An integrated study of Shine's actualized and pure single-subject behavior functions can produce more information than studying only one function. After summarizing the mathematics behind Shine's viewpoint, an ordinary regression analysis approach to the actualized behavior function is integrated with a time-series analysis approach to the pure…

Provides a comparison of centered and raw-score analyses in least squares regression. The two methods are demonstrated with constructed data in a Monte Carlo study to be equivalent, yielding identical hypothesis tests associated with the moderation effect and regression equations that are functionally equivalent. (SLD)