Proposes three different multiple range tests based upon the Newman-Keuls philosophy with respect to significance levels. The three tests utilize the Fmax statistic, Cochran's statistic and a normalizing log transformation of the sample variances respectively. (Author/RC)

A problem in analysis of variance is that after rejection of the overall hypothesis, no contrasts of interest are found to be significant. A procedure for determining the contrast of significance is outlined, and the relationship between the "most significant" contrast and the overall test is shown. (Author/JKS)

A simple rationale for Scheffe's Method and Gabriel's Simultaneous Test Procedure is presented. Examples of both methods are provided. (Author)

An error is described that may occur in a posteriori testing, particularly when the original analysis of variance produces an F ratio that is just barely significant and the computer printout of the analysis does not provide the means that were used in the program. (Author/JKS)

J. P. Shaffer has presented two tests to improve the power of multiple comparison procedures. This article described an algorithm to carry out the tests. The logic of the algorithm and an application to a data set are given. (SLD)

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.…

Two alternative procedures are described for testing the significance of differences of group means. The first consists of a reduction in the critical value when comparing the largest and smallest means. The other alternative uses the unmodified range test without a preliminary F test. An example is provided. (Author/CTM)

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)

Dunnett's procedure for comparing K-1 treatments with a control is discussed within the context of three nonparametric models: those of Kruskal-Wallis, Friedman, and Cochran. (Author/MH)

This study examined the sampling distribution of the analysis of variance F ratio in the two sample cases when it followed a preliminary test for variance equality. When the population variances were equal, the sampling distribution approximated the theoretical F distribution quite well, but not when population variances differed. (JAZ)

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)

Details of a reasonably precise normalization technique for coefficient alpha are outlined, along with methods for estimating the variance of the normalized statistic. These procedures lead to the K-sample significance test. (RC)

Statistics used to estimate the population correlation ratio were reviewed and evaluated. The sampling distributions of Kelly's and Hays' statistics were studied empirically by computer simulation within the context of a three level one-way fixed effects analysis of variance design. (Author/RC)