Setwise regression analysis is a new technique developed to allow a stepwise solution when the interest is in sets of variables rather than in single variables. (CK)

The authors describe a computer program which deals with sets of variables rather than with one variable at a time. (MM)

This description of the technical details required for using the HIER-GRP computer program, which was developed to group or cluster regression equations in an iterative manner so as to minimize the overall loss of predictive efficiency at each iteration, contains a discussion of the basic algorithm, an outline of the essential steps,…

Copies of a complete multiple regression computer program (incorporating the modified Gauss-Jordan procedure) and instructions for its use may be found in the senior author's recent book, The Funstat Package in Fortran IV,'' Holt, Rinehart and Winston. (Authors/CB)

This method of generating multivariate data differs from previous techniques in that it uses Crout factorization to develop the desired variance-covariance matrix. (Author/CK)

Two computer programs (one batch, one interactive) are designed to provide statistics for a weighted linear combination of several component variables. Both programs provide mean, variance, standard deviation, and a validity coefficient. (Author/JKS)

Considerable thought, research, and concern has been expanded in an effort to determine whether the assumption of a quadratic relation between a single predictor and a criterion violated the assumptions which Johnson and Neyman (1936) state for calculating regions of significance about interacting regressions. In particular, there has been special…

A method is developed for testing a priori multiple regression models. The method allows one to specify in advance as many unstandardized or standardized coefficients as one wants to and allows the remaining slopes to be free to vary. (Author/PN)

Four computer programs using the general purpose multiple linear regression program have been developed. Setwise regression analysis is a stepwise procedure for sets of variables; there will be as many steps as there are sets. Covarmlt allows a solution to the analysis of covariance design with multiple covariates. A third program has three…

Joreskog's general method for analysis of covariance structures was developed for estimating a model involving structures of a very general form on means, variances, and covariances of multivariate observations. This method achieves a great deal of generality and flexibility, in that it is capable of handling most standard statistical models as…

The construction and interpretation of confidence intervals for the prediction of new cases in multiple regression analysis is explained. An example is provided. (JKS)

The absence of suitable external criteria is a recurrent problem for test, battery, and inventory developers in selecting items or tests for inclusion in final operational instruments. This report presents a computing algorithm developed for use when no adequate external selection criterion is available. The algorithm uses a multiple linear…

The results of an algorithm which is designed to take a set of commonality coefficients, either real or manipulated, and, if possible, produce one or more sets of regressor correlations that are consistent with them are examined. A number of different ways of resolving the higher order commonality values into their lower orders were tried and the…

Three procedures used to control Type I error rate in stepwise regression analysis are forward selection, backward elimination, and true stepwise. In the forward selection method, a model of the dependent variable is formed by choosing the single best predictor; then the second predictor which makes the strongest contribution to the prediction of…