Description
Book SynopsisCategorical Data Analysis and Multilevel Modeling Using R provides a practical guide to regression techniques for analyzing binary, ordinal, nominal, and count response variables using the R software. Author Xing Liu offers a unified framework for both single-level and multilevel modeling of categorical and count response variables with both frequentist and Bayesian approaches. Each chapter demonstrates how to conduct the analysis using R, how to interpret the models, and how to present the results for publication. A companion website for this book contains datasets and R commands used in the book for students, and solutions for the end-of-chapter exercises on the instructor site.
Trade ReviewThis book provides a highly accessible and practical introduction to some of the most useful regression models in social science research. Most students and applied researchers will find it valuable. -- Yang Cao
This is an excellent book that covers many topics that are given just slight attention in many other books.
-- Ahmed Ibrahim
I would highly recommend this book, especially if readers are beginners. -- Man-Kit Lei
This book provides an engaging and intuitive introduction to maximum likelihood estimation through contemporary examples. -- Jennifer Hayes Clark
Table of ContentsChapter 1. R Basics Chapter 2. Review of Basic Statistics Chapter 3. Logistic Regression for Binary Data Chapter 4. Proportional Odds Models for Ordinal Response Variables Chapter 5. Partial Proportional Odds Models and Generalized Ordinal Logistic Regression Models Chapter 6. Other Ordinal Logistic Regression Models Chapter 7. Multinomial Logistic Regression Models Chapter 8. Poisson Regression Models Chapter 9. Negative Binomial Regression Models and Zero-Inflated Models Chapter 10. Multilevel Modeling for Continuous Response Variables Chapter 11. Multilevel Modeling for Binary Response Variables Chapter 12. Multilevel Modeling for Ordinal Response Variables Chapter 13. Multilevel Modeling for Count Response Variables Chapter 14. Multilevel Modeling for Nominal Response Variables Chapter 15. Bayesian Generalized Linear Models Chapter 16. Bayesian Multilevel Modeling of Categorical Response Variables
