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
- 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 blue-print 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
Table of contents
document with corrections is available. We also updated the GAM code for
recent R versions.
Data and R code
All data files are given below. Use the read.table
function to import the data. For this you need the data in
All R code is provided in a
zip file. We haven given
up compiling a new version of the AED package each time a new R version
comes out. AED only contained data; read.table
does the same.
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:
- 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
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 have 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