Categorical data analysis and multilevel modeling using R /

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 categori...

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Bibliographic Details
Main Author:	Liu, Xing (Education professor) (Author)
Format:	Book
Language:	English
Published:	Thousand Oaks, California : SAGE Publications, [2023].
Subjects:	Multilevel models (Statistics) R (Computer program language)

Table of 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.