000			02070cam a2200181 i 4500
999			_c39377 _d39377
020			_a9781544324906
082	0	0	_a519.0285133 _bXIN-C
100	1		_aLiu, Xing _eauthor.
245	1	0	_aCategorical data analysis and multilevel modeling using R / _cXing Liu,
260			_aLondon; _bSage Publishing _c2023.
300			_axxxiii, 708 p. : _billustrations ;
504			_aIncludes bibliographical references (pages 689-694) and index.
505	0		_aR 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.
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"--
650		0	_aMultilevel models (Statistics)
650		0	_aR (Computer program language)
942			_2ddc _cBK