The robustness with respect to Type I error and the power of a proposed test statistic in testing the conjoint hypotheses of mean and variability equality were examined in this simulation study. The conjoint test utilizes the maximum p-value from separate tests of equality of means and equality of variability as its p-value to control the Type I…

The validity conditions for univariate repeated measures designs are described. Attention is focused on the sphericity (equality of variance) requirement. It is recommended that separate rather than pooled error term procedures be routinely used to test a priori hypotheses. (Author/JKS)

Procedures for the analysis of profiles of means in repeated measures designs under order restriction for patterns of mean change are described. Tables of critical values are provided for the case of simple-order alternatives. (Author/JKS)

This paper briefly describes unplanned and planned methods of evaluating differences between means and explains orthogonal versus nonorthogonal contrasts to help the researcher understand a framework of planned comparisons. A small heuristic data set is generated to illustrate the superiority of planned comparisons over omnibus analysis of…

Factorial analyses differ from nonfactorial analyses in that in the former all possible hypotheses (all possible main effects and interaction effects) are tested regardless of their substantive interest to the researcher and their interpretability, while in the latter, only substantive and interpretable hypotheses are tested. This paper shows the…

The calculation of the F statistic for a one-factor analysis of variance (ANOVA) and the construction of an ANOVA tables are easily implemented on a spreadsheet. This paper describes how to compute the p-value (observed significance level) for a particular F statistic on a spreadsheet. Decision making on a spreadsheet and applications to the…

The use of multiple comparisons in analysis of variance (ANOVA) is discussed. It is argued that experimentwise Type I error rate inflation can be serious and that its influences are often unnoticed in ANOVA applications. Both classical balanced omnibus and orthogonal planned contrast tests inflate experimentwise error to an identifiable maximum.…

Formulae and graphs are presented allowing computation of the variances of three prototypical distributions over a finite number of categories. The uses of the variances of the maximum variance distribution, the uniform distribution and a unimodal triangular distribution to make inferences about distribution shapes are shown in several examples.…

This article reviews some of the less well-known hypothesis tests for variance, how they are employed, and how the results may be interpreted. Tests include testing for a single variance and the T-test for correlated variances. (CT)

Computation of a one-way analysis of variance (ANOVA) "F" ratio from descriptive statistics in the absence of raw data is corrected from two sources. Means associated with inferential statistical hypotheses are identified as estimable population parameters. (Author)

Monte Carlo techniques were employed to compare the familiar F-test with Welch's V-test procedure for testing hypotheses concerning a priori contrasts among K treatments. The two procedures were compared under homogeneous and heterogeneous variance conditions. (Author)

This paper develops a general method for comparing treatment magnitudes for research employing multiple treatment fixed effects analysis of variance designs, which may be used for main effects with any number of levels without regard to directionality. (Author/BS)

Multivariate and univariate analysis of variance methods (MANOVA and ANOVA, respectively) are compared for their relative value in educational research. The favoritism shown multivariate techniques is questioned. Criteria for the selection of the appropriate technique are outlined. The relationships among research hypotheses, statistical…

The literature is reviewed regarding the difference between planned contrasts, OVA and unplanned contrasts. The relationship between statistical power of a test method and Type I, Type II error rates is first explored to provide a framework for the discussion. The concepts and formulation of contrast, orthogonal and non-orthogonal contrasts are…

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…