A method based on three variance computations and some minor arithmetic is presented as an alternative to criterion-scale regression for the computation of a repeated measures-randomized blocks analysis of variance (RMBANOVA). The use of margin sum and cell variances can simplify the analysis of data for RMBANOVA. (SLD)

The univariate and multivariate models for the analysis of covariance are compared for the case where an experimental design contains between and within subject factors, one dependent variable, and one observation per subject. (Author/JKS)

Investigates implications for finite and known item populations for classical test theory, and the alpha coefficient among items in paper-and-pencil testing. (Author/AG)

A study was made of the problem of representing the expectations of mean squares associated with analysis of variance sources of variation for experimental designs. These designs have a factorial structure over repeated measures or, for some other reason, have variates within a factorial design not all of which are mutually independent. A simple…

Games (1973) criticized the Marascuilo and Levin (1970) "nested" or simple effects design as a poor substitute for the usual logic of a factorial analysis of variance. Marascuilo and Levin's use of "nesting" is completely idiosyncratic and contrary to well-established usage, thus confusing the student. Proper usage is…

The effects of variance heterogeneity on the empirical probability of a Type I error for the analysis of variance (ANOVA) F-test are examined. The rate of Type I error varies as a function of the degree of variance heterogeneity, and the ANOVA F-test is not always robust to variance heterogeneity when sample sizes are equal. (Author/JAC)

See EJ 030 376 and also TM 500 285 in this issue. (CK)

The available methods for analyzing and interpreting data with multivariate analysis of variance are reviewed, and guidelines for their use are presented. Causal models that underlie the various methods are presented to facilitate the use and understanding of the methods. (Author/PN)

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…

Simultaneous test procedures (STPS for short) in the context of the unrestricted full rank general linear multivariate model for population cell means are introduced and utilized to analyze interactions in factorial designs. By appropriate choice of an implying hypothesis, it is shown how to test overall main effects, interactions, simple main,…

In the geometrical construct of the MANOVA, the dimensions of interest are primarily those of the significant canonical variates, rather than either those of the original n variables or even the total possible canonical variates. (Authors)