Generalized Linear Mixed Models with Applications in Agriculture and Biology

The book provides an introduction to mixed generalized linear models with applications to the biological sciences, discussing the theory and application of GLMMs and their advantages over linear statistical models. It also highlights the importance of proper training and responsibility in handling and mastering these advanced tools.

Format: Paperback / softback
Length: 427 pages
Publication date: 17 August 2023
Publisher: Springer International Publishing AG

Mixed Generalized Linear Models (MGLMs) are a powerful tool for analyzing data with non-normal distributions and random effects. This open access book provides an introduction to MGLMs with applications to the biological sciences, focusing on an applications perspective while maintaining the rigor of the theory. The book covers the theory behind each method, illustrates its application with examples, and discusses some of the assumptions and shortcomings of linear statistical models. Generalized Linear Models (GLMs) are a popular approach for analyzing response variables with non-normal distributions. GLMs use an exponential family distribution to describe the response data, which can be extended to models with random effects using Generalized Linear Mixed Models (GLMMs). GLMMs have gained significant attention in recent years due to computational advances and improvements in statistical analysis programs. The word "Generalized" refers to non-normal distributions for the response variable, and the word "Mixed" refers to random effects, in addition to the fixed effects typical of analysis of variance (or regression). With the development of modern statistical packages such as Statistical Analysis System (SAS), R, and ASReml, a wide variety of statistical analyzes are available to a wider audience. However, to be able to handle and master more sophisticated models requires proper training and great responsibility on the part of the practitioner to understand how these advanced tools work. GMLM is an analysis methodology used in agriculture and biology that can accommodate non-normal distributions and random effects. It has been applied to a wide range of problems, including crop yield analysis, animal breeding, and ecological studies. The book provides a comprehensive overview of MGLMs, including their theoretical foundations, practical applications, and limitations. It also includes case studies and examples to illustrate the use of MGLMs in real-world scenarios. In conclusion, Mixed Generalized Linear Models (MGLMs) are a valuable tool for analyzing data with non-normal distributions and random effects. This open access book provides an excellent introduction to MGLMs with applications to the biological sciences, focusing on an applications perspective while maintaining the rigor of the theory. The book covers the theory behind each method, illustrates its application with examples, and discusses some of the assumptions and shortcomings of linear statistical models. If you are interested in learning more about MGLMs, this book is a must-read.

Dimension: 235 x 155 (mm)
ISBN-13: 9783031328022
Edition number: 1st ed. 2023