Levin's (1975) sample-size determination procedure for completely randomized analysis of variance designs is extended to designs in which antecedent or blocking variables information is considered. In particular, a researcher's choice of designs is framed in terms of determining the respective sample sizes necessary to detect specified contrasts…

The results of an investigation into some special cases of the general "orthomax" formulation are presented. In particular, the effects of manipulating a parameter in this formulation on various aspects of factor solutions are identified through the use of four sets of data, varying considerably in size, and reliability and factorial complexity of…

Points out that 108 studies in the first 25 volumes of AV Communication Review used univariate analysis of variance to test experimental hypotheses, and suggests that researchers include omega-squared values in their reports to permit estimation of the relationship between x and y variables, and correlation data for comparing studies. (MER)

This paper is an ardent plea for simplifying experimental design and the associated statistics. The emphasis is on design itself. Traditional designs from simple to complex and reviewed and the simplest, most basic ways of handling the data are presented. Design is stressed in such a way that simple statistics follow. The intactness of…

Although there is a healthy trend toward employment of multivariate statistical methods in the analysis of data from experiments in psychology and education which involve multiple dependent variables, there remains a need to demonstrate the wide variety of data analytic techniques available for post hoc analysis of statistically significant…

Fragmented treatment in the literature of the problem of unbalanced data suggests an examination within a single framework of some of the more important issues. (JH)

Data processing problems encountered in a comparative study of teacher roles are discussed. (DB)

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)

A particular strategy for investigating effects from a multivariate analysis of variance (MANOVA) is proposed. The strategy involves multiple two-group multivariate analyses. The analysis strategy is described in detail and illustrated with real data sets. (Author/JKS)

Hollingsworth recently showed a posttest contrast for analysis of variance situations that, for equal sample sizes, had several favorable qualities. However, for unequal sample sizes, the contrast fails to achieve status as a maximized contrast; thus, separate testing of the contrast is required. (Author/GSK)

A program is described utilizing a microcomputer and tape drive with any contingency or chi-square table from 2x2 to 8x8. It requires only the entering of the number of rows and number of columns, plus one-time entry of cell frequencies. (Author/JKS)

It is the purpose of this paper to provide social scientists with some insight in dealing with Type 11 error, that is, the probability of failing to reject a false null hypothesis, and therefore, optimum sample size and number of levels, in the random-effects analysis of variance. (Author/RK)