00000nam a2200000 i 4500 UP-1685675941131649275 Buklod 20250217155443.0 m |o d | ta 250217s2023 cau a b 001 0 eng 9781544324906 (paperback) 22465863 Econ-34588; Mind Mover DLC DECON rda eng QA 278.2 L58 2023 Liu, Xing author. Categorical data analysis and multilevel modeling using R Xing Liu. Los Angeles SAGE [2023]. xxxiii, 708 pages illustrations 24 cm text txt rdacontent unmediated rdamedia volume nc rdacarrier Includes bibliographical references and index. R basics -- Review of basic statistics -- Logistic regression for binary data -- Proportional odds models for ordinal response variables -- Partial proportional odds models and generalized ordinal logistic regression models -- Other ordinal logistic regression models -- Multinomial logistic regression models -- Poisson regression models -- Negative binomial regression models and zero-inflated models -- Multilevel modeling for continuous response variables -- Multilevel modeling for binary response variables -- Multilevel modeling for ordinal response variables -- Multilevel modeling for count response variables -- Multilevel modeling for nominal response variables -- Bayesian generalized linear models -- Bayesian multilevel modeling of categorical response variables. 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 PowerPoint slides and solutions for the end-of-chapter exercises on the instructor site, and datasets and R commands used in the book on the student site"-- Provided by publisher. Multilevel models (Statistics) R (Computer program language) Book FO UPD DECON QA 278.2 L58 2023 Book