• Title: Multivariate Generalized Linear Mixed Models Using R

  Authors: Damon Mark Berridge, Robert Crouchley

• Hardcover:  304 Pages
• Publisher:  the CRC Press
• At The ISBN-10:  1,439,813,264
• 13-ISBN:  978-1439813263
  

Multivariate Generalized Linear Mixed Models the Using R & lt  Presents robust and methodologically Sound Models for the Analyzing Large and Complex Data sets, Enabling Readers to answer increasingly Complex Research Questions. At The Book Applies at The s Principles of Modeling to longitudinal Data from Panel and Related 's Via at The Sabre Software Package Penalty for in R.

The A Unified Framework for A the Broad Class of Models
at The in the authors First Discuss Members of at The Family of Generalized Linear Models, by degrees Adding Complexity to at The Modeling Framework by Incorporating Random Effects. The After reviewing at The Generalized Linear Model Notation, They Illustrate A the 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.

The Improve Your Longitudinal Study
the In Medical and social OF S. & Research, MGLMMs Help disentangle State dependence from incidental the Parameters. The Focusing ON THESE Sophisticated Data the Analysis Techniques, the this Book not Hesitate to at The Statistical Theory and Modeling Involved in longitudinal 's. Many examples Throughout at The text Illustrate at The the Analysis of real-world data sets. Exercises, solutions, and other material are available on a supporting website.

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