An artifact encountered in regression models of human judgment is explored. The direction and magnitude of the artifactual effect is shown to depend upon the nature of the experimental task and task conditions. Use of an alternative index is recommended. (Author/JKS)

The extent to which standardized regression coefficients (beta values) can be used to determine the importance of a variable in an equation was explored. The beta value and the part correlation coefficient--also called the semi-partial correlation coefficient and reported in squared form as the incremental "r squared"--were compared for…

An investigation of the effects of randomly missing data in two-predictor regression analyses is described. The differences in the effectiveness of five common treatments of missing data on estimates of R-squared values and each of the two standardized regression weights is also investigated. Bootstrap sample sizes of 50, 100, and 200 were drawn…

The stepwise regression method of selecting predictors for computer assisted multiple regression analysis was compared with forward, backward, and best subsets regression, using 16 data sets. The results indicated the stepwise method was preferred because of its practical nature, when the models chosen by different selection methods were similar…

A Monte Carlo study was performed to test under what conditions and to what degree various alternatives would be superior to multiple linear regression (MLR). The criteria used was the mean squared error of prediction of individual scores and the mean squared error of estimation of the regression weights. Populations were simulated containing…

The degree of nonorthogonality in a factorial design was systematically increased. Five methods of dealing with nonorthogonality were selected and applied: two were least squares solutions (Method 1 and Method 2); two were approximate solutions (the unweighted means analysis and the method of expected frequencies); and the fifth was the…

Context for the application and specialization of a Bayesian linear model is m-group regression and the application to the prediction of grade point average. Specialization involves the assumption of homogeneity of regression coefficients (but not intercepts) across groups. Model's predictive efficiency is compared with that of the full m-group…

A variety of algorithms for analyzing covariance structures are considered. Additionally, two methods of estimation, maximum likelihood, and weighted least squares are considered. Comparisons are made between these algorithms and factor analysis. (Author/JKS)

Three methods that can be used subsequent to a regression analysis to determine the relative effectiveness of schools are Dyer's Performance Indices, Scheffe's hyperbolic confidence bands, and Gafarian's linear confidence bands. These methods were applied to data from 54 hypothetical schools randomly generated from a multivariate normal…

Two methods of analyzing nonorthogonal (uneven cell sizes) cross-classified data sets are compared. The methods are direct standardization and the general linear model. The authors illustrate when direct standardization may be a desirable method of analysis. (JKS)

Different approaches to defining suppression in multiple regression/correlation are compared, and their differences are illustrated. A test for determining the significance of a suppressor effect, which is based on the definition of suppression of W. F. Velicer, is extended to the general multiple predictor case and analysis of variance. (SLD)

The relationship of multiple linear regression to various multivariate statistical techniques is discussed. The importance of the standardized partial regression coefficient (beta weight) in multiple linear regression as it is applied in path, factor, LISREL, and discriminant analyses is emphasized. The multivariate methods discussed in this paper…

The author's previously developed theory on income distribution, in which two of the explanatory variables are the average level and the distribution of education, is refined and tested on data selected and processed by the author and data from three studies by Americans. The material consists of data on subdivisions of three countries, the United…

The purpose of the study was to develop a linear programming model to be used for prediction, test the accuracy of the predictions, and compare the accuracy with that produced by curvilinear multiple regression analysis. (Author)

To examine and clarify background conditions for understanding variables which affect salary, the salary and compensation programs at two industrial and three educational organizations were subjected to a statistical audit. Data were available on 272 employees. Ten compensation variables were studied as having direct or indirect effects on salary:…