Related Experiment Video
Updated: Mar 26, 2026

Basics of Multivariate Analysis in Neuroimaging Data
Published on: July 24, 2010
Univariate and Multivariate Groups by Trials Analysis Under Violation of Variance-Covariance and Normality
Abstract:
The conventional Groups x Trials F ratio from an analysis of variance (ANOVA) was compared with three alternatives: an epsilon corrected F ratio, a nonparametric test, and a parametric multivariate test. The Type I error rate and power of the tests was investigated under violation of variance-covariance and normality assumptions. In general, the nonparametric test was preferable under violation of the normality assumption. When both normal-theory conditions were met, the conventional F ratio was preferred, but under severe violation of the variance-covariance assumption, the multivariate test was generally preferred.
Related Concept Videos
One-Way ANOVA
Statistical Methods to Analyze Parametric Data: ANOVA
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
What is an ANOVA?
Before performing ANOVA, one must ensure that the samples used for this analysis have three crucial characteristics or statistical assumptions. The first assumption states that the samples should be drawn from normally distributed samples, while the second requires that all the drawn samples should be randomly and...
Comparing the Survival Analysis of Two or More Groups
What is ANOVA?
Before performing ANOVA, one must ensure that the samples used for this analysis have three crucial characteristics or statistical assumptions. The first assumption states that the samples should be drawn from normally distributed samples, while the second requires that all the drawn samples be randomly and independently...
One-Way ANOVA: Equal Sample Sizes
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...

