Methods for the calculation of eta coefficient, or correlation ratio, squared have recently been presented for examining the strength of relationship in univariate analysis of variance. This paper extends them to the multivariate case in which the effects of independent variables may be examined in relation to two or more dependent variables, and…

While the potential use of correlation methods has spread to wide contexts and these uses have permeated behavioral research, their scope remains the orthodox applications: to test independence, and to measure association. It is well worth noticing that problems having no obstensible connection to dependence, independence, or association have been…

Reasons for transforming dependent variable measures for use in analysis of variance is discussed, including nonnormality, heteroscedasticity and scale-induced interactions. It is pointed out that nonlinear transformations change the interpretation of interactions, and a method for reducing heteroscedasticity is described. (Author/RM)

Illustrates how expected mean squares needed in the analysis of variance can be arrived at via the use of only one rule: the expected mean square E(MS) for any source of variation for any ANOVA model is specified effect plus the specified effect in combination with any random effect. (Editor/RK)

Focuses on the procedures available for substituting a special predictive coding method for some of the more complex general regression procedures. (Author)

Estimators which are optimal under assumptions of normality are shown to be vulnerable to the effects of outliers. A survey of robust alternatives is presented. Included are alternatives to the mean, standard deviation, product-moment correlation, t-test, analysis of variance, multivariate techniques, and schemes for outlier detection. (Author/JKS)

In multivariate analysis of variance the canonical variates of one effect may be correlated with the canonical variates of another effect. When the two effects are an interaction and a main effect this correlation interferes with the interpretation of the main effect. When the two effects are both main effects the interpretation of the common…

This article is concerned with estimation of components of maximum generalizability in multifacet experimental designs involving multiple dependent measures. An example of a two-facet partially nested design is provided. (Author/RC)

Focuses on Binomial Effect Size Display (a concept helpful in interpreting size of an experimental effect). Suggests that both statistical significance and explained variance be reported in experimental research and that values for the latter concepts can be viewed with a more accurate perspective by using BESD. (Author/JN)

Variance reduction analysis is a simple method for determining the effect of inequality of cell size on analysis of variance calculations. The suggested procedure has three steps. (Author/CK)

Dependability of class means is analyzed by applying generalizability to a split-plot design with students nested within classes. Basic generalizability concepts are reviewed, and the derivation and interpretation of distinct generalizability concepts are discussed. Four generalizability coefficients are compared with each other and with the three…