Mixed Effects Models and Extensions in Ecology with R Review

Average Reviews:

(More customer reviews)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.

Click Here to see more reviews about: Mixed Effects Models and Extensions in Ecology with R

This book discusses advanced statistical methods that can be used to analyse ecological data. Most environmental collected data are measured repeatedly over time, or space and this requires the use of GLMM or GAMM methods. The book starts by revising regression, additive modelling, GAM and GLM, and then discusses dealing with spatial or temporal dependencies and nested data.

Get 20% OFF

Click here for more information about Mixed Effects Models and Extensions in Ecology with R