Beyond Multiple Linear Regression: Applied Generalized Linear Models And Multilevel Models in R

This book covers generalized linear models and correlated data methods, with case studies and R code. It is suitable for graduate non-statistics majors or advanced undergraduate statistics majors.

\n Format: Hardback
\n Length: 418 pages
\n Publication date: 18 December 2020
\n Publisher: Taylor & Francis Inc
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Generalized linear models (GLMs) and correlated data methods are essential tools in statistical analysis, enabling us to model and analyze a wide range of data structures. This comprehensive textbook offers a unified discussion of these models and methods, making it suitable for graduate non-statistics majors or advanced undergraduate statistics majors.

The book begins by introducing the basic concepts of GLMs and correlated data methods, including the linear model, the generalized linear model, and the generalized additive model. It then goes on to cover more advanced topics such as mixed models, hierarchical models, and Bayesian methods.

Throughout the textbook, real-world case studies are used to illustrate the practical applications of these models and methods. These case studies cover a diverse range of fields, including biology, economics, and social sciences, and provide students with hands-on experience in applying statistical techniques to real-world data.

In addition to its theoretical coverage, the textbook also includes material on R, a popular programming language for statistical analysis. At the end of each chapter, there are R code examples that demonstrate how to implement the statistical techniques discussed in that chapter. This makes the textbook an invaluable resource for students who want to learn both the theory and the practical application of statistical analysis using R.

Furthermore, the textbook includes a solutions manual that provides detailed solutions to all the exercises and problems in the book. This manual is designed to help students reinforce their understanding of the material and improve their problem-solving skills.

Overall, this textbook is an excellent resource for students who want to gain a comprehensive understanding of generalized linear models and correlated data methods. Its comprehensive coverage, real-world case studies, and emphasis on practical applications make it suitable for both undergraduate and graduate students in statistics and related fields.

\n Weight: 796g\n
Dimension: 242 x 158 x 33 (mm)\n
ISBN-13: 9781439885383\n \n