Generalized Linear Models for Categorical and Continuous Limited Dependent Variables

This new book was designed for graduate students and researchers in the behavioral, social, health, and medical sciences, this text employs generalized linear models, including mixed models, for categorical and limited dependent variables.
 
BOCA RATON, Fla. - Sept. 25, 2013 - PRLog -- Designed for graduate students and researchers in the behavioral, social, health, and medical sciences, this text employs generalized linear models, including mixed models, for categorical and limited dependent variables. Categorical variables include both nominal and ordinal variables. Discrete or continuous limited dependent variables have restricted support, whether through censorship or truncation or by their nature. The book incorporates examples of truncated counts, censored continuous variables, and doubly bounded continuous variables, such as percentages.

BOOK Features
Provides extensive coverage of continuous limited dependent variables, including material on doubly bounded variables
Presents a thorough and consistent treatment of over-dispersion and heteroscedasticity, including tests for them and techniques for modeling them
Integrates coverage of "boundary inflation" issues such as zero inflation in counts and zero or one inflation in proportions
Highlights extensions of models to include mixed models and Bayesian MCMC estimation
Includes worked examples using the R environment, focusing on packages such as VGAM and betareg

For more information on this new title, please visit http://www.crcpress.com/product/isbn/9781466551732

ISBN 9781466551732, September 5, 2013, 308pp
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