The complexity of relationships between variables in a variety of rehabilitation settings can be appropriately addressed by the use of multivariate methods of statistical analysis. The purpose of this article is to describe (a) some basic concepts and principles of multivariate methods as well as (b) common misconceptions in the application of such methods. Specifically, the authors focus on th...

We have developed an adaptation of multi-variate analysis of variance (MANOVA) to analyze statistically both local and global patterns of multi-electrode array (MEA) electrophysiology data where the activities of many (typically >100) neurons have been recorded simultaneously. Whereas simple application of standard MANOVA techniques prohibits extraction of useful information in this kind of dat...

MOTIVATION Oligonucleotide arrays such as Affymetrix GeneChips use multiple probes, or a probe set, to measure the abundance of mRNA of every gene of interest. Some analysis methods attempt to summarize the multiple observations into one single score before conducting further analysis such as detecting differentially expressed genes (DEG), clustering and classification. However, there is a risk...

We propose analysis of information in speech using three sources-language (phone), speaker and channeL Information in speech is measured as mutual information between the source and the set of features extracted from speech signaL We assume that distribution of features can be modeled using Gaussian distribution. The mutual information is computed using the results of analysis of variability in...

We consider random n× n matrices of the form (XX∗ + Y Y ∗)− 1 2 Y Y ∗ (XX∗ + Y Y ∗)− 1 2 , where X and Y have independent entries with zero mean and variance one. These matrices are the natural generalization of the Gaussian case, which are known as MANOVA matrices and which have joint eigenvalue density given by the third classical ensemble, the Jacobi ensemble. We show that, away from the spe...

Multivariate Analysis of Variance (MANOVA) is a popular statistical tool in the social sciences, allowing for the comparison of mean vectors across groups. MANOVA rests on three primary assumptions regarding the population: (a) multivariate normality, (b) equality of group population covariance matrices and (c) independence of errors. When these assumptions are violated, MANOVA does not perform...