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Generalized Linear Models

Generalized Linear Models
A Unified Approach

Second Edition

June 2019 | 176 pages | SAGE Publications, Inc

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

Series Editor's Introduction
About the Authors
1. Introduction
Model Specification  
Prerequisites and Preliminaries  
Looking Forward  
2. The Exponential Family
Derivation of the Exponential Family Form  
Canonical Form  
Multi-Parameter Models  
3. Likelihood Theory and the Moments
Maximum Likelihood Estimation  
Calculating the Mean of the Exponential Family  
Calculating the Variance of the Exponential Family  
The Variance Function  
4. Linear Structure and the Link Function
The Generalization  
5. Estimation Procedures
Estimation Techniques  
Profile Likelihood Confidence Intervals  
Comments on Estimation  
6. Residuals and Model Fit
Defining Residuals  
Measuring and Comparing Goodness-of-Fit  
Asymptotic Properties  
7. Extentions to Generalized Linear Models
Introduction to Extensions  
Quasi-Likelihood Estimation  
Generalized Linear Mixed Effects Model  
Fractional Regression Models  
The Tobit Model  
A Type-2 Tobit Model with Stochastic Censoring  
Zero Inflated Accomodating Models  
A Warning About Robust Standard Errors  
8. Conclusion
Related Topics  
Classic Reading  
Final Motivation  
9. References

Sample Materials & Chapters

2. The Exponential Family

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ISBN: 9781506387345