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Mixed Effects Models and Extensions in Ecology With R (Anglais) Relié – 1 mars 2009

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Building on their previous book on the subject, the authors provide an expanded introduction to using Regression to analyze ecological data. As with the earlier book, real data sets from postgraduate ecological studies or research projects are used throughout.

--Ce texte fait référence à l'édition Broché .

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Format: Relié
Ce livre très complet aborde à la fois les aspects fondamentaux des analyses statistiques en écologie, avec une petite dose de maths pour comprendre ce qu'il y a derrière (pour ceux que ça intéresse), mais aussi les aspects plus techniques (code sous R, sélection de modèles, etc.)
Indispensable pour les étudiants et chercheurs qui veulent faire des analyses "justes" en se dépatouillant des corrélations spatiales ou temporelles.
You must have it !!!
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Format: Relié Achat vérifié
Will make you love statistics and feel able to use them even if you don't have a strong background and don't feel really comfortable with the maths behind. Many real life example with accompanying R code, making it concrete and even more understandable. A must have and read book, together with the amazing 2007 'Analysng Ecological Data'. I *enjoy* reading these books!
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Commentaires client les plus utiles sur Amazon.com (beta)

Amazon.com: 4.6 étoiles sur 5 18 commentaires
3 internautes sur 3 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 A pleasure to read 26 juin 2012
Par C. Andersen - Publié sur Amazon.com
Format: Relié Achat vérifié
I've read through the first 6 chapters during the past few days, and have quite enjoyed it -- it reads smoothly, almost like a novel; quite unexpected for a text written by multiple authors. There's even a bit of humor. I've worked a bit with mixed models in the SAS world, but needed to learn how to deal with them in R, and this book has turned-out to be rather better than expected in this regard (I'm really liking how mixed models are done in R as opposed to SAS). At first I thought the blend of topics covered a bit odd, wondering what the heck a "Generalized Additive Model" was and what it was doing in a book on mixed models, but it turns out that GAMs are really nifty and not too difficult to grasp and in fact appear relevant to problems I'm currently working on. The authors have a preference for working with the distribution of the data as given rather than attempting to transform it to an approximation of normality, and I'm coming to appreciate this as well. For an applied text, it has unexpected depths. Great book.
15 internautes sur 15 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Very nice applied text 12 juillet 2009
Par Philip Turk - Publié sur Amazon.com
Format: Relié Achat vérifié
Many applications in ecology clearly are not amenable to use of the general linear model due to violations of its assumptions. In fact, in most projects I work on, things like correlation among the errors, nonconstant error variance, etc., are the rule, rather than the exception. If you are looking for an applied text dealing with these types of situations with lots of examples, and demonstrations on analysis in R, then you should get this book. It does not delve into theory; there are plenty of other textbooks where you can fill in those details if you are interested. Rather, this book would be ideally suited for quantitative ecologists, biometricians, and statistical consultants who work in life sciences. Another nice thing is that the book does not assume you are an "R expert". Well done.
7 internautes sur 7 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 Excellent Book, too many typos 15 décembre 2009
Par Amazon Customer - Publié sur Amazon.com
Format: Relié Achat vérifié
This book is very good in both introducing statistical concepts and describing the R commands to implement those concepts. It is required, however, a relatively deep understanding of Linear Regression. I read this book from A to Z, however, each chapter is as independent as possible, and therefore it is possible to read the individual chapters. I did not try the code on the web page of the book yet, but I did type some of the examples and the code from the book works OK. In addition in the web site there is a set of instructions to install a package with all the code from the examples and updates on the R libraries and packages explained in the book.

Each methodology explained in the book covers step by step both the statistical (and mathematical) details as well as the construction of the R code (including importing the dataset and formating of columns for later analysis).

One of the most important "extra points" in this book is the use of a consistent methodology to approach the problem of modeling ecological data from a statistical point of view.

My only complain is that there are lots (LOTS) of typos, nothing too serious (since I was able to catch them) but still, I'm a little disappointed, because a good reviewer should got those.
3.0 étoiles sur 5 Nice Intermediate Book 1 septembre 2013
Par Salvador A. Gezan - Publié sur Amazon.com
Format: Relié Achat vérifié
Many ecologists recommended this book and as I statistician I decided to give it a go. I have read a few chapters and they are quite interesting. I think the inclusion of new authors to this team improved the quality of their statistics. The concepts are good, and I follow a very similar philosophy than the authors in my consulting. However, I was missing some additional discussion in relevant topics including extensions on hierarchical models and other complex mixed models with several strata. The elements are there but not in the best form. I do congratulate the authors in adding some of those chapter with detailed examples and with code and data! This provides a great way to get the experience for the reader, and I am glad the editors accepted this approach. In summary, this book is a good start, but it should be complemented with other books, for example Littell et al. (2006) that is in SAS but provides great descriptions of concepts to a similar level.
5.0 étoiles sur 5 Another Great Book by Zuur and Company 2 novembre 2009
Par Martin L. Jones - Publié sur Amazon.com
Format: Relié Achat vérifié
I really enjoyed this group's first book, Analysing Ecological Data, but this book is even better. The second book follows the style and format of the first book in that the authors explain the concepts in non-technical terms, but don't gloss over the important ideas. Moreover, they use real data sets that are quite messy and they show how these data sets can be analyzed through the numerous case studies in the text. All of the case studies are from published ecological papers or PhD theses. What makes this book even better than their first is that R code is included in the text and they carefully show how R can be used to help with the analysis and to construct the elaborate and beautiful graphics displayed in the text. If you're looking to analyze your own ecological data, you must have a copy of this book. It is an invaluable resource both for statistical methodology and for understanding how to use R with statistical models. These guys have done a spectacular job with this book and I look forward to future work from them.
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