This paper reviews issues involved in converting continuous variables to nominal variables to be used in the OVA techniques. The literature dealing with the dangers of dichotomizing continuous variables is reviewed. First, the assumptions invoked by OVA analyses are reviewed in addition to concerns regarding the loss of variance and a reduction in…

Analysis of variance (ANOVA) was invented in the 1920s to partition variance of a single dependent variable into uncorrelated parts. Having uncorrelated parts makes the computations involved in ANOVA incredibly easier. This was important before computers were invented, when calculations were all done by hand, and also were done repeatedly to check…

Aptitude-treatment interaction (ATI) studies have been used with some frequency, yet many researchers do not understand fully what interaction effects are. Because the means for interactions involve fewer persons per mean, power to detect interaction effects is typically smallest for the highest-order interaction in a given design. This phenomenon…

The correlation coefficient is an integral part of many other statistical techniques (analysis of variance, t-tests, etc.), since all analytic methods are actually correlational (G. V. Glass and K. D. Hopkins, 1984). The correlation coefficient is a statistical summary that represents the degree and direction of relationship between two variables.…

A hypothesized data set is used to illustrate that canonical correlation analysis is a general linear model, subsuming other parametric procedures as special cases. Specific techniques included in analyses are t tests, Pearson correlation, multiple regression, analysis of variance, multivariate analysis of variance, and discriminant analysis. (SLD)

Commonality analysis is a method of partitioning variance that has advantages over more traditional "OVA" methods. Commonality analysis indicates the amount of explanatory power that is "unique" to a given predictor variable and the amount of explanatory power that is "common" to or shared with at least one predictor…

A small multivariate data set is used to illustrate the usefulness of structure coefficients when interpreting results of educational experiments. Data are analyzed using a multivariate analysis of variance (MANOVA), and results are interpreted in three different ways to determine the contribution of individual variables to prediction: (1) using…

H. Levene (1960) proposed a heuristic test for heteroscedasticity in the case of a balanced two-way layout, based on analysis of variance of absolute residuals. Conditions under which design imbalance affects the test's characteristics are identified, and a simple correction involving leverage is proposed. (SLD)

Using a hypothetical data set of 24 cases concerning opinions on contemporary issues on which Democrats and Republicans might disagree, concrete examples are provided to illustrate that canonical correlation analysis is the most general linear model, subsuming other parametric procedures as special cases. Specific statistical techniques included…

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…

Although an analysis of covariance (ANCOVA) allows for the removal of an uncontrolled source of variation that is represented by the covariates, this "correction," which occurs with the dependent variable scores is unfortunately seen by some as a blanket adjustment device that can be used with an inadequate amount of consideration for…

Various realizations have led to less frequent use of the "OVA" methods (analysis of variance--ANOVA--among others) and to more frequent use of general linear model approaches such as regression. However, too few researchers understand all the various coefficients produced in regression. This paper explains these coefficients and their…

Describes two invariance tests, the jackknife procedure and Procrustean rotation, and applies them in a discriminant analysis for this heuristic study. Invariance testing helps to prevent overemphasis on findings of statistical significance and overgeneralization of a research result, and thus is gaining favor as an indicator of result importance.…

There are advantages to using a priori or planned comparisons rather than omnibus multivariate analysis of variance (MANOVA) tests followed by post hoc or a posteriori testing. A small heuristic data set is used to illustrate these advantages. An omnibus MANOVA test was performed on the data followed by a post hoc test (discriminant analysis). A…

One hundred undergraduate students at a large southern university were the subjects of a study to determine whether the persuasion process encompasses two mutually exclusive strategies--systematic or heuristic processing of information--or whether the two processes are, in fact, independent. Subjects participated in groups of about l5 and were…