Midlands State University Library
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Categorical data analysis and multilevel modeling using R / Xing Liu, Eastern Connecticut State University.

By: Material type: TextTextPublisher: SAGE, [2023]Description: xxxiii, 708 pages : illustrations ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781544324906
Subject(s): LOC classification:
  • QA278.2 LIU
Contents:
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.
Summary: "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"--
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Holdings
Item type Current library Call number Copy number Status Date due Barcode
Book Book Main Library Open Shelf QA278.2 LIU (Browse shelf(Opens below)) 161632 Available BK149509

Includes bibliographical references (pages 689-694) 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"--

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