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 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 \textttR package \textttGLMpack. All links are available at www.sagepub.com/gill2e.
Publications by Type: Book
2019
Gill, Jeff, and Michelle Torres. Generalized Linear Models: A Unified Approach. Second Ed, Thousand Oaks, CA: Sage, 2019.
2014
SInce the Spring of 2016 all of the code and data for the book has been located in the R package BaM, including both R and JAGS. Answers to odd numbered exercises are here. The Corrected index for the very first print run (few people will need this). The state.df dataset got left off the BaM package so it’s here. The errata for the third edition are here.
2008
Gill, Jeff. Bayesian Methods: A Social and Behavioral Sciences Approach. 2nd ed., Cambridge University Press, 2008.
2006
Gill, Jeff. Essential Mathematics for Political and Social Research, Cambridge University Press, 2006.
2003
Gill, Jeff, Micah Altman, and Michael McDonald. Numerical Issues in Statistical Computing for the Social Scientist, John Wiley & Sons, 2003.
2002
2000
Gill, Jeff, and Kenneth Meier. What Works, A New Approach to Program and Policy Analysis, Routledge, 2000.
