Multivariate Generalized Linear Mixed Models Using R - Hardcover

Berridge, Damon Mark; Crouchley, Robert

Hardcover

ISBN 10: 1439813264 ISBN 13: 9781439813263

Publisher: CRC Press, 2011

Synopsis

Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data from panel and related studies via the Sabre software package in R.

A Unified Framework for a Broad Class of Models
The authors first discuss members of the family of generalized linear models, gradually adding complexity to the modeling framework by incorporating random effects. After reviewing the generalized linear model notation, they illustrate a range of random effects models, including three-level, multivariate, endpoint, event history, and state dependence models. They estimate the multivariate generalized linear mixed models (MGLMMs) using either standard or adaptive Gaussian quadrature. The authors also compare two-level fixed and random effects linear models. The appendices contain additional information on quadrature, model estimation, and endogenous variables, along with SabreR commands and examples.

Improve Your Longitudinal Study
In medical and social science research, MGLMMs help disentangle state dependence from incidental parameters. Focusing on these sophisticated data analysis techniques, this book explains the statistical theory and modeling involved in longitudinal studies. Many examples throughout the text illustrate the analysis of real-world data sets. Exercises, solutions, and other material are available on a supporting website.

About this title

Product Description

Multivariate Generalized Linear Mixed Models Using R To provide researchers with the ability to analyze large and complex data sets using robust models, this book presents a unified framework for a broad class of models that can be applied using a dedicated R package (Sabre). It includes chapters that cover the analysis of multilevel models using univariate generalized linear mixed models (GLMMs). Full description

Review

I think this is a very well organised and written book and therefore I highly recommend it not only to professionals and students but also to applied researchers from many research areas such as education, psychology and economics working on complex and large data sets.
―Sebnem Er, Journal of Applied Statistics, 2012

Edition details

• Publisher: CRC Press
• Publication date: 2011
• ISBN 10: 1439813264
• ISBN 13: 9781439813263
• Binding: Hardcover
• Language: English
• Edition number: 1
• Number of pages: 304