Mixed Effects Models and Extensions in Ecology with R
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In this book the authors provide an expanded introduction to using regression and its extensions in analysing ecological data. The first part of the
book is a largely non-mathematical introduction to linear mixed effects modelling, 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 analysing 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 analysing the reader's own data.
These chapters provide an invaluable insight into analysing 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 analysing the reader's own data.
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