Mixed Effects Models and Extensions in Ecology with R (2009). Zuur, Ieno, Walker, Saveliev and Smith. Springer

Building on the successful Analyzing Ecological Data (2007) by Zuur, Ieno and Smith, the authors now provide an expanded introduction to using regression and its extensions in analyzing ecological data. As with the earlier book, real data sets from postgraduate ecological studies or research projects are used throughout. The first part of the book is a largely non-mathematical introduction to linear mixed effects modeling, GLM and GAM, zero inflated models, GEE, GLMM and GAMM. The second part provides ten case studies that range from koalas to deep sea research. These chapters provide an invaluable insight into analyzing complex ecological datasets, including comparisons of different approaches to the same problem. By matching ecological questions and data structure to a case study, these chapters provide an excellent starting point to analyzing your own data. Data and R code from all chapters are available. Order from Springer or Amazon.com

Book reviews

Table of contents



A word document with corrections is available. We also updated the GAM code for recent R versions.

Data, R code and AED package 

In the book we use the package AED to load data. However, we haven given up compiling a new version of the AED package each time a new R version comes out. Therefore we no longer provide AED. As an alternative:

> Birdies <- read.table(file = "C:/YourDirectory/Blahblah.txt, header = TRUE, dec = ".")   

> source("C:/YourDirectory/HighstatLibV6.R")


All R code for all chapters is provided in a zip file.

UPDATE 24 August 2009: The R code for the GAM sections have been updated. It now runs on R 2.9.1.   

Note the following statement:

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