Xing Liu, professor of education at Eastern Connecticut State University, recently released his second book, “Categorical Data Analysis and Multilevel Modeling Using R.” The release follows his first book, “Applied Ordinal Logistic Regression Using Stata,” and provides a broader coverage of regression models using R.

R is a programming language for statistical computing that is used by data miners and statisticians for data analysis and developing statistical software.

Liu, who specializes in educational assessment and research, said his new book was inspired by the work of colleagues and graduate students who he interacts with at conferences. “I was often asked questions like, can R perform this type of analysis? Do you know if there are any packages in R that have a similar function to the program introduced in your paper? Their questions motivated me to work on an R book on categorical data analysis and multilevel modeling.”

Liu has previously published articles in the Journal of Modern Applied Statistical Methods (JMASM). He has also received the Excellence Award in Creativity and Scholarship at Eastern. Liu continues to work with data analysis and its advancements, using the skills and knowledge he acquired in earning his PhD from the University of Connecticut in measurement, evaluation and assessment in educational psychology.

Liu hopes that his book is used to help expand the minds of graduate students studying data analysis. “I hope that readers learn about modern regression techniques from this book for analyzing categorical and count response variables with R, the free, open-source statistical software.” He continued by saying, “I hope that readers can use the R code from the book and apply these models with the code for their own research.”

Materials from this book are a potential resource for the new Data Science major at Eastern, said Liu. He plans to continue with his research and explore topics including categorical data, multilevel modeling and Bayesian methods.

The book, which was published in late February of 2022, has received a number of positive reviews. Ahmed Ibrahim, senior research consult at Johns Hopkins University, said, “This is an excellent book that covers many topics that are given just slight attention in many other books.” Associate Professor of Political Science at the University of Houston Jennifer Clark, said the book “provides an engaging and intuitive introduction to maximum likelihood estimation through contemporary examples.”