The robustness of the statistic for complex contrasts in analysis of variance is compared to the statistic developed by Welch. The Welch statistic is recommended as the benchmark test for complex contrasts. (Author/JKS)

Illustrates a simple nonparametric alternative that can be used to test a hypothesis that two proximity matrices on the same set of variables or objects reflect a similar pattern of high and low entries. (RC)

Disagreements have arisen about the robustness of the t test in normal populations with unequal variances. Employing liberal but objective standards for assessing robustness, it is shown that the t test is not always robust to the assumption of equal population variances even when sample sizes are equal. (Author/JKS)

Two stage multiple-comparison procedures give an exact solution to problems of power and Type I errors, but require equal sample sizes in the first stage. This paper suggests a method of evaluating the experimentwise Type I error probability when the first stage has unequal sample sizes. (Author/BW)

Discusses difficulties encountered in use of the Scheffe procedure to locate the most significant parametric function within a linear statistical model that has been tested and rejected by, for example, analysis of variance. A solution to the problems is presented. (TJH)

This paper is concerned with testing hypotheses about main effects, simple effects, and interaction effects by means of analysis of variance. It presents alternative strategies for analyzing data sets for which a factorial model with two completely crossed, fixed factors is appropriate. (CTM)

When the variance assumptions of a repeated measures ANOVA are not met, the F distribution of the mean square ratio should be adjusted by the sample estimate of the Box correction factor. An alternative is proposed which is shown by Monte Carlo methods to be less biased for a moderately large factor. (RC)

Using computer simulation, parametric analysis of covariance (ANCOVA) was compared to ANCOVA with data transformed using ranks, in terms of proportion of Type I errors and statistical power. Results indicated that parametric ANCOVA was robust to violations of either normality or homoscedasticity, but practiced significant power differences favored…

The method of unweighted means in the multivariate analysis of variance with unequal sample sizes was investigated. By approximating the distribution of the hypothesis sums-of-squares-and-cross-products with a Wishart distribution, multivariate test statistics were derived. Monte Carlo methods and a numerical example illustrate the technique.…

Compares three methods of analyzing pairwise treatment differences in a multi-treatment experiment via computer simulation techniques. Under the equal n condition, the robustness of the conventional Tukey Wholly Significant Difference test (WSD) to heterogeneous variances was contrasted with two alternate techniques. Under unequal n conditions,…

It is shown that using formulae for the estimation of sampling errors based on simple random sampling, when a design actually involves cluster sampling, can lead to serious underestimation of error. Jackknife and balanced repeated replication are recommended as techniques for dealing with this problem. (Author/CTM)

The use of statistical methods to combine the results of independent empirical research studies (metanalysis) has a long history, with work mainly divided into tests of the statistical significance of combined results and methods for combining estimates across studies. Methods of metanalysis and their applications are reviewed. (SLD)