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Generalized Linear Models for Categorical and Continuous Limited Dependent Variables (Paperback)
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Generalized Linear Models for Categorical and Continuous Limited Dependent Variables (Paperback)
Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences
Expected to ship within 12 - 17 working days
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Generalized Linear Models for Categorical and Continuous Limited
Dependent Variables is designed for graduate students and
researchers in the behavioral, social, health, and medical
sciences. It incorporates examples of truncated counts, censored
continuous variables, and doubly bounded continuous variables, such
as percentages. The book provides broad, but unified, coverage, and
the authors integrate the concepts and ideas shared across models
and types of data, especially regarding conceptual links between
discrete and continuous limited dependent variables. The authors
argue that these dependent variables are, if anything, more common
throughout the human sciences than the kind that suit linear
regression. They cover special cases or extensions of models,
estimation methods, model diagnostics, and, of course, software.
They also discuss bounded continuous variables, boundary-inflated
models, and methods for modeling heteroscedasticity. Wherever
possible, the authors have illustrated concepts, models, and
techniques with real or realistic datasets and demonstrations in R
and Stata, and each chapter includes several exercises at the end.
The illustrations and exercises help readers build conceptual
understanding and fluency in using these techniques. At several
points the authors bring together material that has been previously
scattered across the literature in journal articles, software
package documentation files, and blogs. These features help
students learn to choose the appropriate models for their purpose.
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