Categorical Data Analysis and Multilevel Modeling Using R
- Xing Liu - Eastern Connecticut State University
Quantitative Methods | Quantitative Research Methods in Education | Quantitative Research Methods in Education | Regression & Correlation | Statistics - General Interest | Statistics in Political Science | Statistics in Political Science | Statistics in Sociology | Structural Equation Modeling, Hierarchical Linear Modeling, & Multilevel Modeling
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.
This 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.
This is an excellent book that covers many topics that are given just slight attention in many other books.
I would highly recommend this book, especially if readers are beginners.
This book provides an engaging and intuitive introduction to maximum likelihood estimation through contemporary examples.
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.
Sage College Publishing
