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Categorical data analysis and multilevel modeling using R /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Categorical data analysis and multilevel modeling using R /Xing Liu.
Author:	Liu, Xing
Description:	xxxiii, 708 pages :illustrations ;24 cm
Subject:	Multilevel models (Statistics)
ISBN:	9781544324906$qpaperback

Categorical data analysis and multilevel modeling using R /
Liu, Xing(Education professor),

Categorical data analysis and multilevel modeling using R /Xing Liu. - xxxiii, 708 pages :illustrations ;24 cm

Includes bibliographical references (pages 689-694) and index.

R basics --

"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"--

ISBN: 9781544324906$qpaperback

LCCN: 2022001572Subjects--Topical Terms:

240063
Multilevel models (Statistics)

LC Class. No.: QA278.2 / .L586 2023

Dewey Class. No.: 519.5/402855133

Categorical data analysis and multilevel modeling using R /
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020 $z 9781544324883$qelectronic book
020 $z 9781544324890$qelectronic book
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100 1 $a Liu, Xing $c (Education professor), $e author. $3 966353
245 1 0 $a Categorical data analysis and multilevel modeling using R / $c Xing Liu.
264 1 $a Thousand Oaks, California : $b SAGE Publications, Inc., $c [2023]
264 4 $c �2023
300 $a xxxiii, 708 pages : $b illustrations ; $c 24 cm
336 $a text $b txt $2 rdacontent
337 $a unmediated $b n $2 rdamedia
338 $a volume $b nc $2 rdacarrier
504 $a Includes bibliographical references (pages 689-694) and index.
505 0 0 $t R basics -- $t Review of basic statistics -- $t Logistic regression for binary data -- $t Proportional odds models for ordinal response variables -- $t Partial proportional odds models and generalized ordinal logistic regression models -- $t Other ordinal logistic regression models -- $t Multinomial logistic regression models -- $t Poisson regression models -- $t Negative binomial regression models and zero-inflated models -- $t Multilevel modeling for continuous response variables -- $t Multilevel modeling for binary response variables -- $t Multilevel modeling for ordinal response variables -- $t Multilevel modeling for count response variables -- $t Multilevel modeling for nominal response variables -- $t Bayesian generalized linear models -- $t Bayesian multilevel modeling of categorical response variables.
520 $a "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"-- $c Provided by publisher.
650 0 $a Multilevel models (Statistics) $3 240063
650 0 $a R (Computer program language) $3 210846
650 6 $a Mod�eles multiniveaux (Statistique) $3 966331
650 6 $a R (Langage de programmation) $3 943796
758 $i has work: $a CATEGORICAL DATA ANALYSIS AND MULTILEVEL MODELING USING R (Text) $1 https://id.oclc.org/worldcat/entity/E39PCXgkqQtGFcpfxRGJBrrkj3 $4 https://id.oclc.org/worldcat/ontology/hasWork
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