Generalized Linear Models for Categorical and Continuous Limited Dependent Variables

Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is a book for graduate students and researchers in the behavioral, social, health, and medical sciences that covers topics such as truncated counts, censored continuous variables, and doubly bounded continuous variables. It provides broad coverage of models and types of data, with examples and demonstrations in R and Stata. The authors argue that these dependent variables are more common in the human sciences than linear regression and discuss special cases, estimation methods, model diagnostics, and software.

Format: Paperback / softback
Length: 308 pages
Publication date: 21 January 2023
Publisher: Taylor & Francis Ltd

Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is a comprehensive resource designed for advanced students and researchers in the behavioral, social, health, and medical sciences. It delves into the realm of statistical analysis, offering a comprehensive framework for modeling and understanding data with categorical and continuous limited dependent variables. The book provides a broad yet unified coverage of the subject matter, seamlessly integrating concepts and ideas across different models and types of data. The authors argue that these dependent variables, which include truncated counts, censored continuous variables, and doubly bounded continuous variables such as percentages, are more prevalent in the human sciences than the traditional linear regression models.

To address this, the book offers a comprehensive treatment of special cases, extensions, estimation methods, model diagnostics, and software. It also explores bounded continuous variables, boundary-inflated models, and techniques for modeling heteroscedasticity, providing valuable insights into the complexities of data analysis.

Throughout the text, the authors employ real or realistic datasets and demonstrations in R and Stata to illustrate concepts, models, and techniques. Each chapter concludes with a series of exercises, designed to reinforce the understanding and application of the discussed topics. These exercises not only help readers develop a deeper conceptual understanding but also enhance their fluency in using these techniques.

Furthermore, the authors have taken the initiative to consolidate material that has previously been scattered across various literature sources, including journal articles, software package documentation files, and blogs. This feature not only enhances the accessibility of the information but also empowers students to choose the most appropriate models for their specific research purposes.

In summary, Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is an essential resource for advanced students and researchers seeking to expand their knowledge and expertise in statistical analysis. With its comprehensive coverage, real-world examples, and practical exercises, this book equips readers with the tools and techniques necessary to effectively model and analyze data with categorical and continuous limited dependent variables, enabling them to make meaningful contributions to their respective fields.

Weight: 570g
Dimension: 234 x 156 (mm)
ISBN-13: 9781032477466