The authors performed a Monte Carlo simulation to empirically investigate the robustness and power of 4 methods in testing mean differences for 2 independent groups under conditions in which 2 populations may not demonstrate the same pattern of nonnormality. The approaches considered were the t test, Wilcoxon rank-sum test, Welch-James test with…

Tests of the equality of variances are sometimes used on their own to compare variability across groups of experimental or non-experimental conditions but they are most often used alongside other methods to support assumptions made about variances. A new nonparametric test of equality of variances is described and compared to current "gold…

This article presents a method for addressing the self-selection bias of students who participate in learning communities (LCs). More specifically, this research utilizes equivalent comparison groups based on selected incoming characteristics of students, known as bootstraps, to account for self-selection bias. To address the differences in…

We propose a nonparametric (or distribution-free) procedure for testing the equality of several population variances (or scale parameters). The proposed test is a modification of Bakir's (1989, Commun. Statist., Simul-Comp., 18, 757-775) analysis of means by ranks (ANOMR) procedure for testing the equality of several population means. A proof is…

Four nonparametric alternatives to the parametric Bartlett test are presented for handling the K-sample equality of variance problem. The two sample Siegel-Tukey Test, Mood Coefficient of Alienation Test, and Klotz Test are extended to the multisample situation by the methods of Puri. A fourth alternative involving a Q-statistic procedure…

Researchers are often in a dilemma as to whether parametric or nonparametric procedures should be cited when assumptions of the parametric methods are thought to be violated. Therefore, the Kruskal-Wallis test and the ANOVA F-test were empirically compared in terms of probability of a Type I error and power under various patterns of mean…

Questions are raised concerning differences between traditional metric multiple regression, which assumes all variables to be measured on interval scales, and nonmetric multiple regression. The ordinal model is generally superior in fitting derivation samples but the metric technique fits better than the nonmetric in cross-validation samples.…

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)

Two estimators of effect size that are based on the sample quartiles are proposed and studied. One is for the situation where a treatment effect is evaluated against a control group, and the other is for a situation in which two parallel treatments are compared. Both are illustrated and evaluated. (SLD)

Examines the similarity between the coordinates which resulted when correlations were used as similarity measures and the factor loadings obtained by factor analyzing the same correlation matrix. Real data, a set of error free data, and some computer generated data containing deliberately introduced sampling error are analyzed. (RC)

Three nonparametric alternatives to the parametric Bartlett test are presented for handling the K-sample equality of variance problem. The two-sample Siegel-Tukey test, Mood test, and Klotz test are extended to the multisample situation by Puri's methods. These K-sample scale tests are illustrated and compared. (Author/GDC)