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Generalized Linear Models
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Generalized Linear Models
A Unified Approach

Second Edition


July 2019 | 144 pages | SAGE Publications, Inc
Generalized Linear Models by Jeff Gill and Michelle Torres explains the theoretical underpinnings of these models so that researchers can decide how to select the best way to adapt their data for this type of analysis. Examples are provided to illustrate the application of GLM to actual data. The Second Edition includes new examples (such a voting intentions in the 2016 U.S. Republican Presidential Primaries); strengthens material on the exponential family form, including a new discussion on multinomial distribution; add more information on how to interpret results and make inferences in the chapter on estimation procedures, and adds a new section on extensions to generalized linear models. A website for the book include software, scripts, supporting documentation, data for the examples, and some extended mathematical derivations.
 
Series Editor's Introduction
 
About the Authors
 
Acknowledgements
 
1. Introduction
Model Specification  
Prerequisites and Preliminaries  
Looking Forward  
 
2. The Exponential Family
Justification  
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  
Distributions  
 
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  
Summary  
 
8. Conclusion
Summary  
Related Topics  
Classic Reading  
Final Motivation  
 
9. References

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ISBN: 9781506387345
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