Beginner's Guide to GLM and GLMM with R.  Zuur AF, Hilbe JM and Ieno EN

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Outline

 This book presents Generalized Linear Models (GLM) and Generalized Linear Mixed Models (GLMM) based on both frequency-based and Bayesian concepts. Using ecological data from real-world studies, the text introduces the reader to the basics of GLM and mixed effects models, with demonstrations of binomial, gamma, Poisson, negative binomial regression, and beta and beta-binomial GLMs and GLMMs. 

The book uses the functions glm, lmer, glmer, glmmADMB, and also JAGS from within R. JAGS results are compared with frequentist results.

R code to construct, fit, interpret, and comparatively evaluate models is provided at every stage. Otherwise challenging procedures are presented in a clear and comprehensible manner with each step of the modelling process explained in detail, and all code is provided so that it can be reproduced by the reader.  

Readers of this book have free access to:

See the Preface (and the text below) how to access the pdfs of these chapters.

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The paperback is priced at 49 GBP. Click to order the book.    

Copyright statement

This book is copyright material from Highland Statistics Ltd. Scanning this book (or parts of it) and distributing the digital media (including uploading to the Internet) without our explicit permission is copyright infringement. Infringing copyright is a criminal offence and you will be taken to court and run the risk of paying ALL damages and compensation. The maximum punishment for copyright infringement in the UK is £5,000.00 (GBP). Highland Statistics Ltd. actively polices against copyright infringement.

Data sets and R code used in the book. Video files

Video file with general comments Alain Zuur

All data sets used in the book are provided as *.txt or *.xls files. Right-mouse click on a data file and click on Save-As.
R code for each chapter is password protected. The password is given on page vi in the preface of the book. See the paragraph "Data sets and R code used in this book"
 
Support routines that we source in various chapters: HighstatLibV6.R  and  MCMCSupportHighstat.R.
Just copy these two files in the working directory (use Save As) and type:
source(file = "HighstatLibV6.R")

source(file = "MCMCSupportHighstat.R")
pdf file with some simple explanations on matrix notation
 
Chapter Title Data sets R code* Video files
1 Introduction to generalized linear models Baileyetal2008.xls
WorkerBees.xls
DrugMites.xls
Chapter1.R.zip 5 July
2 Generalized linear modelling applied to red squirrel data RedSquirrels.txt Chapter2.R.zip 5 July
3 GLM applied to presence-absence polychaeta data PolychaetaV3.txt Chapter3.R.zip 5 July
4 Introduction to mixed effects models Spiders.txt Chapter4.R.zip 5 July
5 GLMM applied to honeybee pollination data pollen.txt Chapter5.R.zip 5 July
6 GLMM for strictly positive data: biomass of rainforest trees seedling.txt Chapter6.R.zip 5 July
7 Binomial, Beta-binomial, and Beta GLMM applied to Cheetah Data Cheetah.txt Chapter7.R.zip 5 July
 
Discussion board
Join the Discussion board (for free) to ask questions on the book chapters. 
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Support chapters

Rather than reproducing the material on MCMC, we give the reader of this book electronic access to Chapter 1 of Zuur et al. (2012a), which contains an introduction to Bayesian statistics and MCMC. Chapter 1 of Zuur (2012b) provides an introduction to multiple linear regression, which is also prerequisite knowledge for this book. These two chapters are downloadable from:

Both chapters are password protected. The password is given on page vi in the preface. See the paragraph labelled "Chapter 1 of Zuur et al. (2012a) and Zuur (2012b)".