We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models, designed to handle multivariate response variables, along with a wide ...

J. Zhu, J. C. Eickhoff, P. Yan, Generalized Linear Latent Variable Models for Repeated Measures of Spatially Correlated Multivariate Data, Biometrics, Vol. 61, No. 3 ...

Researchers and students of applied statistics and the social and behavioral sciences will find this book indispensable for understanding both general linear model theory and application. The model is ...

A generalized linear model is currently considered to be the most appropriate for ordinal data analysis method because, using a simple link function, we can adopt theory and methodology developed ...

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative ...