The One-way Analysis of Variance (ANOVA) is a procedure for testing the hypothesis that K population means are equal, where K > 2. The One-way ANOVA compares the means of the samples or groups in order to make inferences about the population means. The One-way ANOVA is also called a single factor analysis of variance because there is only one independent variable or factor. The independent vari...

analysis of variance (ANOVA): one-way nested, hierarchical two-way linear model fixed, random, and mixed models factorial arrangement of treatments variance components sum of squares, mean square, expected mean square sampling fraction, fixed effects, random effects simple effects, main effects, interaction effects, additive effects analysis of covariance, covariate, concomitant variable data t...

In this paper we derive asymptotic tests for general linear hypotheses on variance components using repeated variance components models In two examples the two way nested classi cation model and the two way crossed classi cation model with interaction we explicitly investigate the properties of the asymptotic tests in small sample sizes

This paper is concerned with the distributions of some test statistics for a multivariate linear hypothesis under nonnormality. The test statistics considered include the likelihood ratio statistic, the Lawley-Hotelling trace criterion and the BartlettNanda-Pillai trace criterion, under normality. We derive asymptotic expansions of the null distributions of these test statistics up to the order...

Research in the behavioral and health sciences frequently involves the application of one-factor analysis of variance models. The goal may be to compare several independent groups of subjects on a quantitative dependent variable or to compare measurements made on a single group of subjects on different occasions or under different conditions. In analyzing data of this kind, it is usually of int...

Seven test statistics known to be robust to the combined effects of nonnormality and variance heterogeneity were compared for their sensitivity to detect treatment effects in a one-way completely randomized design containing four groups. The six Welch-James-type heteroscedastic tests adopted either symmetric or asymmetric trimmed means, were transformed for skewness, and used a bootstrap method...