: Includes mathematical appendices covering matrix algebra, probability calculus, and statistical inference to assist readers with the necessary background.
: For handling non-normal response variables.
: Important definitions and key statements are highlighted in concise summary boxes for quick reference. Regression: Models, Methods and Applications
: The book provides a cohesive framework that covers parametric, non-parametric, and semi-parametric regression models. Broad Scope of Models : It includes detailed discussions on:
: Selection of methods is heavily influenced by the availability of user-friendly statistical software, making it highly practical for researchers. : The book provides a cohesive framework that
: Advanced tools that do not require strict functional forms.
: A flexible framework for modeling complex data structures. : A flexible framework for modeling complex data structures
: Theoretical concepts are reinforced with numerous real-world data examples and case studies from social, economic, and life sciences.