Analysis of Categorical Data with R by Christopher R. Bilder – A Practical Guide for Statistical Modeling

Introduction

In the growing landscape of data science and statistical research in India, the ability to analyze categorical data accurately has become an essential skill for students, researchers, and professionals alike. Analysis of Categorical Data with R by Christopher R. Bilder offers a comprehensive and practical guide to understanding and applying modern categorical data analysis techniques using the R programming language. Published by CRC Press, this hardcover edition is an indispensable resource for anyone looking to master the analysis of binary, multicategory, and count response variables through real-world examples and hands-on coding.

Book Overview

This book bridges the gap between theoretical foundations and practical implementation, making it ideal for both beginners and experienced statisticians. It covers everything from basic concepts like odds ratios and probability estimation to advanced model building and assessment. The author emphasizes the use of R as both a data analysis tool and a learning aid, enabling readers to simulate data, test assumptions, and evaluate model performance. With numerous examples drawn from medicine, psychology, sports, ecology, and other fields, the book ensures that readers can directly apply the techniques to their own research or professional projects.

Key Highlights

• No prior R experience required – The book starts with a gentle introduction to R, making it accessible to students and professionals new to programming.
• Extensive R code and output – Every method is accompanied by reproducible R code, allowing readers to follow along and practice.
• Data simulation for deeper understanding – Readers learn to simulate data to grasp underlying assumptions and evaluate procedure performance.
• Graphical demonstrations – Visualizations are used extensively to illustrate features, properties, and diagnostic checks.
• Real-world examples – Case studies from medicine, psychology, sports, ecology, and more provide context and relevance.

Inside the Book

The book is structured to guide readers from fundamental concepts to advanced applications. Early chapters cover the basics of categorical data, contingency tables, and measures of association. Subsequent sections delve into logistic regression, multinomial models, Poisson regression, and methods for handling overdispersion. Each chapter includes detailed R code, annotated output, and interpretation of results. Special attention is given to model selection, goodness-of-fit tests, and graphical diagnostics. The use of simulation-based learning helps readers develop a robust intuition for statistical reasoning.

Key Topics

• Binary response models and logistic regression
• Multicategory and ordinal response models
• Count data analysis using Poisson and negative binomial regression
• Contingency table analysis and exact tests
• Model building, selection, and validation
• Handling overdispersion and zero-inflated data
• Graphical methods for categorical data
• Simulation-based inference and bootstrap methods

Reader Benefits

By working through this book, readers will gain the confidence to analyze their own categorical datasets using R. The hands-on approach ensures that theoretical knowledge is immediately translated into practical skills. The book’s emphasis on simulation and graphical exploration helps readers understand why certain methods work and when to apply them. Additionally, the inclusion of diverse examples makes the content relatable for Indian students and researchers working in fields like public health, social sciences, agriculture, and marketing. The hardcover format is durable for frequent use, whether in a library, lab, or classroom.

Learning Outcomes

Upon completing this book, readers will be able to: perform comprehensive exploratory analysis of categorical data; fit and interpret logistic regression, multinomial, and count models; assess model fit using diagnostics and simulation; apply appropriate methods for overdispersed or sparse data; create publication-quality graphics for categorical data; and make informed decisions about which statistical techniques to use in real-world scenarios. The skills acquired are directly transferable to research, industry, and academic settings.

Who Should Read

This book is ideal for postgraduate students in statistics, biostatistics, data science, and related disciplines. It is also highly valuable for researchers in medicine, psychology, ecology, epidemiology, and social sciences who regularly encounter categorical data. Professionals working in market research, quality control, or policy analysis will find the practical examples and R code immediately useful. Instructors looking for a textbook for a course on categorical data analysis will appreciate the clear structure and ready-to-use teaching materials.

About the Author

Christopher R. Bilder is a Professor of Statistics at the University of Nebraska-Lincoln. With extensive experience in categorical data analysis and statistical computing, he has published numerous research articles and developed widely used R packages. His teaching philosophy emphasizes clarity, reproducibility, and real-world relevance, all of which are reflected in this book. Dr. Bilder’s expertise ensures that readers receive accurate, up-to-date, and practical guidance.

About the Publisher

CRC Press is a premier global publisher of scientific, technical, and medical content. Known for its high-quality textbooks and reference works in statistics and data science, CRC Press ensures that this book meets rigorous academic standards. The hardcover edition is built to last, making it a valuable addition to any personal or institutional library.

Conclusion

Analysis of Categorical Data with R is more than just a textbook; it is a practical companion for anyone serious about data analysis. With its blend of theory, simulation, and hands-on R coding, it equips readers with the tools to tackle real-world categorical data challenges. Whether you are a student, researcher, or professional, this book will deepen your understanding and enhance your analytical capabilities. Order your copy from Bookshops.in today and take a decisive step toward mastering categorical data analysis with R.