Generalized Linear Models
eBook - ePub

Generalized Linear Models

A Unified Approach

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Generalized Linear Models

A Unified Approach

About this book

Generalized Linear Models: A Unified Approach provides an introduction to and overview of GLMs, with each chapter carefully laying the groundwork for the next. The Second Edition provides examples using real data from multiple fields in the social sciences such as psychology, education, economics, and political science, including data on voting intentions in the 2016 U.S. Republican presidential primaries. The Second Edition also strengthens material on the exponential family form, including a new discussion on the multinomial distribution; adds more information on how to interpret results and make inferences in the chapter on estimation procedures; and has a new section on extensions to generalized linear models.

Software scripts, supporting documentation, data for the examples, and some extended mathematical derivations are available on the authors' websites as well as through the \texttt{R} package \texttt{GLMpack}. Supporting material (data and code) to replicate the examples in the book can be found in the ?GLMpack? package on CRAN or on the website&


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Yes, you can access Generalized Linear Models by Jeff Gill,Michelle Torres in PDF and/or ePUB format, as well as other popular books in Social Sciences & Social Science Research & Methodology. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Series
  4. Publisher Note
  5. Title Page
  6. Copyright Page
  7. CONTENTS
  8. Series
  9. Contributors
  10. Chapter 1. Introduction
  11. Chapter 2. The Exponential Family
  12. Chapter 3. Likelihood Theory and the Moments
  13. Chapter 4. Linear Structure and the Link Function
  14. Chapter 5. Estimation Procedures
  15. Chapter 6. Residuals and Model Fit
  16. Chapter 7. Extensions to Generalized Linear Models
  17. Chapter 8. Conclusion
  18. References
  19. Index