The present study was addressed to the group AOV situation. Onte Carlo methods were employed to contrast several procedures with respect to a. ) control over Type 1 errors and b. ) power. (Editor)

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)

The equivalence of one-way multivariate analysis of variance and canonical correlation is well known. The usefulness of canonical correlation analysis is performing factorial multivariate analysis of variance is demonstrated. (Author)

The use of analysis of covariance in simple repeated measures designs is considered. Conditions necessary for the analysis of covariance adjusted main effects and interactions to be meaningful are presented. (Author/JKS)

Repeated measures designs have traditionally been analyzed by the univariate mixed model approach, in which the repeated measures effect is tested against an error term based on the subject by treatment interaction. This paper considers an extension of this analysis to designs in which the individual repeated measures are multivariate. (Author/JKS)

The Journal of Counseling Psychology for 1970-1979 was searched, and values of n (analysis of variance) were computed on each univariate inferential statistic reported. Frequency distributions compiled for the values of n2 revealed that the median strength of association value for research reported was .0830. (Author)

The results of an extensive analysis of the statistical methodology employed by researchers whose manuscripts were published in the first twelve volumes of the "Educational Administration Quarterly" are reported. (Author)

The interpretation of significant left-tailed analysis of variance (ANOVA) F-ratios is supported by considering the case of a fixed effects ANOVA model. The conclusions of this case are generalizable to other standard ANOVA models. (Author/PN)

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…

This volume contains the five major addresses and subsequent discussion from the Symposium on the General Linear Models Approach to the Analysis of Experimental Data in Educational Research, which was held in 1967 in Athens, Georgia. The symposium was designed to produce systematic information, including new methodology, for dissemination to the…

Many researchers assume that unequal cell frequencies in analysis of variance (ANOVA) designs result from poor planning. However, there are several valid reasons why one might have to analyze an unequal-n data matrix. The present study reviewed four categories of methods for treating unequal-n matrices by ANOVA: (a) unaltered data (least-squares…

The assumptions and consequences of applying conventional and newer statistical methods to meta-analytic data sets are reviewed. The application of the two approaches to a meta-analytic data set described by L. V. Hedges (1984) illustrates the differences. Hedges analyzed six studies of the effects of open education on student cooperation. The…

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…

This article discusses M. Rosenberg's Test-Factor Standardization as a type of marginal standardization. To illustrate this relation, the author utilizes a table on abortion attitudes formerly published by K.W. Smith in his commentary on Rosenberg's work. (Author/GC)

Results indicated that availability of categories rather than frequency of words seemed most crucial in determining developmental changes in clustering efficiency. (Authors)