: Advanced tools that do not require strict functional forms.
: A flexible framework for modeling complex data structures.
: For handling non-normal response variables. Regression: Models, Methods and Applications
: Includes mathematical appendices covering matrix algebra, probability calculus, and statistical inference to assist readers with the necessary background.
: Written at an intermediate mathematical level, the text is accessible to students and practitioners with basic knowledge of calculus and probability. : Advanced tools that do not require strict functional forms
The second edition of this textbook was released in 2021 by Springer , expanding its coverage of contemporary regression techniques. Regression: Models, Methods and Applications - Amazon.com
: Selection of methods is heavily influenced by the availability of user-friendly statistical software, making it highly practical for researchers. Regression: Models, Methods and Applications - Amazon
: Important definitions and key statements are highlighted in concise summary boxes for quick reference.