Bi-linear matrix-variate analyses, integrative hypothesis tests, and case-control studies

Hypothesis Tests for Neyman’s Bias in Case-Control Studies

Survival bias is a long-recognized problem in case-control studies, and many varieties of bias can come under this umbrella term. We focus on one of them, termed Neyman’s bias or “prevalence-incidence bias.” It occurs in case-control studies when exposure affects both disease and disease-induced mortality, and we give a formula for the observed, biased odds ratio under such conditions. We compa...

Matrix-Variate Discriminative Analysis, Integrative Hypothesis Testing, and Geno-Pheno A5 Analyzer

A general perspective is provided on both on hypothesis testing and discriminative analyses, by which matrix-variate discriminative analyses are proposed based on the matrix normal distribution, featured by a bi-linear extension of Fisher linear discriminant analysis and a further extension to binary variables. Moreover, a general formulation is proposed for integrative hypothesis testing and f...

A New Control Chart to Monitor Mean Shifts of Bi-Variate Quality Control Processes

Matrix-Variate Beta Generator - Developments and Application

Matrix-variate beta distributions are applied in different fields of hypothesis testing, multivariate correlation analysis, zero regression, canonical correlation analysis and etc. A methodology is proposed to generate matrix-variate beta generator distributions by combining the matrix-variate beta kernel with an unknown function of the trace operator. Several statistical characteristics, exten...

Matrix-variate Beta Distribution

We propose matrix-variate beta type III distribution. Several properties of this distribution including Laplace transform, marginal distribution and its relationship with matrix-variate beta type I and type II distributions are also studied.