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Categorical Data Analysis and Multilevel Modeling Using R by Xing Liu 2023
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A book with obvious wear. May have some damage to the cover but integrity still intact. The binding may be slightly damaged but integrity is still intact. Possible writing in margins, possible underlining and highlighting of text, but no missing pages or anything that would compromise the legibility or understanding of the text.
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Located in: Gardena, California, United States
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eBay item number:266745450569
Item specifics
- Condition
- ISBN
- 9781544324906
About this product
Product Identifiers
Publisher
SAGE Publications, Incorporated
ISBN-10
1544324901
ISBN-13
9781544324906
eBay Product ID (ePID)
11050420509
Product Key Features
Number of Pages
744 Pages
Publication Name
Categorical Data Analysis and Multilevel Modeling Using R
Language
English
Subject
Methodology, General, Statistics
Publication Year
2022
Type
Textbook
Subject Area
Mathematics, Social Science
Format
Trade Paperback
Dimensions
Item Height
1 in
Item Weight
41.1 Oz
Item Length
9 in
Item Width
7.5 in
Additional Product Features
Intended Audience
College Audience
LCCN
2022-001572
Dewey Edition
23
Reviews
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. -- 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.
Illustrated
Yes
Dewey Decimal
519.536
Table Of Content
Chapter 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
Synopsis
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. 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 Number
QA278.2
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