This article concerns the power of various data analytic strategies to detect the effect of a single genetic variant (GV) in multivariate data. We simulated exactly fitting monozygotic and dizygotic phenotypic data according to single and two common factor models, and simplex models. We calculated the power to detect the GV in twin 1 data in an ANOVA of phenotypic sum scores, in a MANOVA, and i...

This paper considers testing the equality of multiple high-dimensional mean vectors under dependency. We propose a test that is based on a linear transformation of the data by the precision matrix which incorporates the dependence structure of the variables. The limiting null distribution of the test statistic is derived and is shown to be the extreme value distribution of type I. The convergen...

All too often researchers perform a Multivariate Analysis of Variance (MANOVA) on their data and then fail to fully recognize the true multivariate nature of their effects. The most common error is to follow the MANOVA with univariate analyses of the dependent variables. One reason for the occurrence of such errors is the lack of clear pedagogical materials for identifying and testing the multi...

MOTIVATION Gene class testing (GCT) or gene set analysis (GSA) is a statistical approach to determine whether some functionally predefined sets of genes express differently under different experimental conditions. Shortcomings of the Fisher's exact test for the overrepresentation analysis are illustrated by an example. Most alternative GSA methods are developed for data collected from two exper...

ABSTRACT In this paper, we have used SAS software for the multivariate analysis of repeated measures data due to Grizzel and Allen (1969). We have applied four multivariate methods viz MANOVA, Profile Analysis, non-parametric multisample rank sum test and non-parametric multisample median test to analyse two sets of data. The findings of the study reveal that profile analysis gives similar resu...