The recognition that all parametric methods are interrelated, coupled with the notion that structure coefficients are often vital in factor and canonical analyses, suggests that structure coefficients may be important in univariate analysis as well. Using a small, heuristic data set, this paper discusses the importance of structure coefficients…

Multiple regression analysis (MRA) may be used when both continuous and categorical variables are included as independent research variables. The use of MRA with categorical variables involves dummy coding, that is, assigning zeros and ones to levels of categorical variables. Caution is urged in results interpretation. (Author/CH)

Analysis of variance (ANOVA) and multiple regression are two of the most commonly used methods of data analysis in behavioral science research. Although ANOVA was intended for use with experimental designs, educational researchers have used ANOVA extensively in aptitude-treatment interaction (ATI) research. This practice tends to make researchers…

The value of variance is emphasized, and the element of design, frequently not adequately understood, is clarified to underscore the importance of variance to the researcher. Two analytic methods, analysis of variance (ANOVA) and multiple regression, are discussed in terms of how each uses/applies variance. Advantages and major difficulties with…

A dichotomous dependent variable is used to determine a combination of variables that will predict group membership. Dichotomous variables are frequently encountered in multiple regression analysis. However, several textbooks question the appropriateness of using multiple regression analysis when analyzing dichotomous dependent variables. The…

Use of analysis of covariance or multiple regression can lead to Type I errors in pretest-posttest nonequivalent control group designs. Analysis of the interaction term of a repeated model analysis of variance was shown to help identify areas of significant change. The standardized difference score, effect size, suggested meaningful differences.…

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 federally funded longitudinal field study called Management Implications of Team Teaching (MITT) required a search for an appropriate strategy for analyzing through-time relationships among selected variables. The MITT project used questionnaires and interviews to collect data concerning the work, governance, attitudes, and orientation of…

This study investigated William Schutz's three-dimensional theory of interpersonal behavior and compatibility (FIRO) to determine its validity as a group measure of compatibility. Data were collected from 248 students enrolled in a multi-section course in small group communications at a large midwestern university. Subjects self-selected…

The current state of usage of regression models in analysis of variance (ANOVA) designs is empirically examined, and examples of several statistical errors made in usage are presented. The assumptions of the general linear model are that all predictors are known without error of measurement and are fixed with no replication or sample variation; in…

Addresses three issues concerning the assessment of the overrating and underrating of academic competence: (1) the impossibility of separating effects of overrating and underrating from effects of perceived and actual competence; (2) the questionable validity of Connell and Ilardi's method; and (3) the proposal of a new method and its implications…