Ridge regression is an approach to the problem of large standard errors of regression estimates of intercorrelated regressors. The effect of ridge regression on the estimated squared multiple correlation coefficient is discussed and illustrated. (JKS)

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)

The use of interaction and non-linear terms in multiple regression poses problems for determining parsimonious models. Several computer programs for using these terms are discussed. (JKS)

Fifteen examples using different formulas for calculating degrees of freedom for power analysis of multiple regression designs worked out by Cohen are presented, along with a more general formula for calculating such degrees of freedom. (Author/JKS)

Path analysis is a data analytic technique for estimating the strengths of hypothesized relationships among a group of variables for a particular sample. Strategies for the use of path analysis are discussed in detail in this extensive article. (JKS)

The analytical procedure of path analysis is described in terms of its use in nonexperimental settings in the social sciences. The description assumes a moderate statistical background on the part of the reader. (JKS)

Historical regression uses the assumption that without intervention, growth at post-test will proceed at the same rate as at pre-test. Several methods of historical regression are compared with an illustrative example. (JKS)

With even the simplest bivariate regression, least-squares solutions are inappropriate unless one assumes a priori that reciprocal effects are absent, or at least implausible. While this discussion is limited to bivariate regression, the issues apply equally to multivariate regression, including stepwise regression. (Author/CTM)

A model for research on teacher effects in which the variance in student outcome post-test performance is attributed to pre-test perfomance; to separate construct domains of student, instructional, and teacher variables; and to interactions between variables in these three construct domains is presented and tested. (Author/JKS)