You are here

Categorical Data Analysis and Multilevel Modeling Using R
Share
Share

Categorical Data Analysis and Multilevel Modeling Using R



February 2022 | 744 pages | SAGE Publications, Inc

Categorical 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 at https://edge.sagepub.com/liu1e contains datasets and R commands used in the book for students, and solutions for the end-of-chapter exercises on the instructor site.



 
Chapter 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

Textbook is both engaging and informative. Your textbook meets both of these criteria.

The text is well-written and easy to understand. The authors have done a great job of explaining complex concepts in a clear and concise way. The text is also well-organized, which makes it easy for students to find the information they need.

Dr Sherif Osman
Business Administration Dept, Univ New Brunswick-Fredericton
June 3, 2023