About this product

Product Identifiers

PublisherSAGE Publications, Incorporated

ISBN-101544324901

ISBN-139781544324906

eBay Product ID (ePID)11050420509

Product Key Features

Number of Pages744 Pages

Publication NameCategorical Data Analysis and Multilevel Modeling Using R

LanguageEnglish

SubjectMethodology, General, Statistics

Publication Year2022

TypeTextbook

Subject AreaMathematics, Social Science

AuthorXing Liu

FormatTrade Paperback

Dimensions

Item Height1 in

Item Weight41.1 Oz

Item Length9 in

Item Width7.5 in

Additional Product Features

Intended AudienceCollege Audience

LCCN2022-001572

ReviewsThis 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, This is an excellent book that covers many topics that are given just slight attention in many other books.

Dewey Edition23

IllustratedYes

Dewey Decimal519.536

Table Of ContentChapter 1. R BasicsChapter 2. Review of Basic StatisticsChapter 3. Logistic Regression for Binary DataChapter 4. Proportional Odds Models for Ordinal Response VariablesChapter 5. Partial Proportional Odds Models and Generalized Ordinal Logistic Regression ModelsChapter 6. Other Ordinal Logistic Regression ModelsChapter 7. Multinomial Logistic Regression ModelsChapter 8. Poisson Regression ModelsChapter 9. Negative Binomial Regression Models and Zero-Inflated ModelsChapter 10. Multilevel Modeling for Continuous Response VariablesChapter 11. Multilevel Modeling for Binary Response VariablesChapter 12. Multilevel Modeling for Ordinal Response VariablesChapter 13. Multilevel Modeling for Count Response VariablesChapter 14. Multilevel Modeling for Nominal Response VariablesChapter 15. Bayesian Generalized Linear ModelsChapter 16. Bayesian Multilevel Modeling of Categorical Response Variables

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. It 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., 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 contains datasets and R commands used in the book for students, and solutions for the end-of-chapter exercises on the instructor site.

LC Classification NumberQA278.2