Mixed Effects Models and Extensions in Ecology with R (2009)

Zuur, Ieno, Walker, Saveliev, Smith


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.


Data, R code and AED package

In the book, we use the package AED to load data. However, we have 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:

  • Download the data files. This is a ZIP file with all data sets. Unzip this file.
  • Use the read.table function to import the data into R. This will be something like: 

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

  • You may need to replace the point by a comma in the dec argument.
  •  To run the corvif function and the pairplot with the Pearson correlation coefficients, download the file HighstatLibV10.R (use right-mouse click and Save As), save it to your computer and in R type:

> source("C:/YourDirectory/HighstatLibV10.R")

  • Replace YourDirectory by the directory in which you saved the file. On a Mac, omit the C: bit.
  • R code for all chapters is provided in a zip file.
  • The provided R code with this book is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. The code is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.


Book reviews

  • Basic and Applied Ecology (2009). Bernd Gruber: ....... This multitude of examples makes this book unique in the statistical literature on mixed models and many readers will find a suitable example that serves as a blueprint for analyzing their own data.........I highly recommend the book to anyone who is familiar with basic statistics such as t-tests, analysis of variance and who wants to expand his/her statistical knowledge to analyze ecological data.
  • A very nice review in the Journal of Statistical Software from Aaron Christ.


Table of contents



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


 Comments from readers

  • ... I have been using your book Mixed Effects Models and Extensions in Ecology with R. I would just like to tell you that it has been extremely useful and easy to understand for me as a non-statistician, and provided excellent guidelines! I will most definitely be using it many more times! Thank you very much! Regards, Michelle Greve. Aarhus University. Aarhus. Denmark
  • I am writing just to let you know that you did a great job with "Mixed effect model and extensions in ecology with R". A very useful, easy-to-read, and highly applicable book (best thing: readable at night without falling asleep -) )!! All the best, Thomas Cherico Wanger. University of Adelaide, Australia
  • I have to compliment you on writing such clear and easy-to-understand statistics books. I have now the full set and find them very useful. They are in stark contrast to some really awful statistics books I have bought on Amazon where the authors seem to have just completed a brain dump without thought nor care as to how anyone would be able to follow their words! Neil Fletcher. University of Aberdeen, UK.