Commentary is presented on the preceding articles in this issue of the journal. Critical commentary is made article by article, and some general recommendations are made. (See TM 503 664 through 670). (JKS)

The problem of selecting regression variables using cost criteria is considered. A method is presented which approximates the optimal solution of one of several criterion functions which might be employed. Examples are given and the results are compared with the results of other methods. (Author/JKS)

Researchers have generally assumed overall job satisfaction to be an additive function of weighted job satisfaction facet scores. This paper considers the linear compensatory model as well as two nonlinear alternatives. Available from: Ramon J. Aldag, University of Wisconsin, 1155 Observatory Drive, Madison, Wisconsin 53706. (Author)

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…

The causal model approach used in this study tested the cumulative hierarchical structure of the six major taxonomic levels of Bloom's Taxonomy by measuring the strengths of the linear relationships ( links'') between levels. (Editor)

The proposed method has the advantage of being a rational procedure which reduces the larger set of variables'' down to a desired subset of predictor variables. The selected subset, then, can be coded for a full regression run if it contains multiple level category variables among those selected. (Author)

Discusses the techniques used in one empirical study of the economies of scale in school districts, and demonstrates that empirical findings based on techniques of this type should not be considered to justify expenditure per student differentials or consolidations to reduce per pupil costs, based on economies of scale. (JF)

A printout of the program and sample output will be provided by the authors upon request. (Authors/CB)

Bounds for the multiple correlation of common factors with the items which comprise those factors are developed. It is then shown that under broad, but not completely general, conditions, the circumstances under which an infinite item domain does or does not perfectly determine selected subsets of its common factors. (Author/JKS)

Recent theoretical analyses of the concept of suppression are identified and discussed. A generalized definition of suppression is presented and the conditions for suppressor structures in the context of the General Linear Model are derived. (Author)

A method is presented for the construction of an artificial data set which will illustrate the behavior of the traditional, the negative, and the reciprocal suppressor variable in multiple regression analysis. It extends the method of Dayton (1972) and includes the previously reciprocal suppression defined by Conger (1974). (Author)

The perfunctory use of factor scores in conjunction with regression analysis is inappropriate for many purposes. It is suggested that factoring methods are most suitable for independent variable sets when some consideration has been given to the nature of the domain, which is implied by the predictors. (Author/BW)