Books

2019

Gill, Jeff, and Michelle Torres. Generalized Linear Models: A Unified Approach. Second Ed, Thousand Oaks, CA: Sage, 2019.

Publisher's Version

Abstract

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.

2014

Gill, Jeff. Bayesian Methods: A Social and Behavioral Sciences Approach. 3rd ed., CRC Press, 2014.

Publisher's Version

Abstract

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.

Purchase Online

2006

Gill, Jeff. Essential Mathematics for Political and Social Research, Cambridge University Press, 2006.

Publisher's Version

Manuscript Contents Listing and Preface: PDF, Errata, Answers to odd-numbered exercises.

2003

Gill, Jeff, Micah Altman, and Michael McDonald. Numerical Issues in Statistical Computing for the Social Scientist, John Wiley & Sons, 2003.

Publisher's Version

Reviews:

"A compact guide to the voluminous literature on optimisation, numerical analysis, and computational statistics. This is no small achievement." - Statistical Software Newsletter in Computational Statistics and Data Analysis.

"…an excellent text. It has the potential to be enormously influential across the social sciences…It should be required reading for everyone who performs statistical computing at the advanced level…" - Journal of the American Statistical Association, June 2005

Other reviews: Technometrics Review, ACM Review, SciTech Book News Review, Choice Review, Computational Statistics and Data Analysis Review, Journal of Statistical Software Review, Statistical Methods in Medical Research Review, Journal of Statistical Computation and Simulation Review.

2002

Gill, Jeff. Bayesian Methods: A Social and Behavioral Sciences Approach, CRC Press, 2002.

Reviews:

"...easily the most comprehensive, scholarly, and thoughtful book the subject... it will do much to promote the use of Bayesian methods." -David Blackwell, University of California, Berkeley.

"A surprisingly thorough review written by a user of Bayesian statistics, with applications drawn from the social sciences." -Persi Diaconis, Stanford University.

"This book is a brilliant and importantly very accessible introduction to the concept and application of Bayesian approaches to data analysis. The clear strength of the book is in making the concept practical and accessible, without necessarily dumbing it down. It therefore retains the richness and complexity of this approach. The coverage is also remarkable, especially discussing this approach in the context of hierarchical linear models." -S V Subramanian, Harvard University.

2000

Gill, Jeff. Generalized Linear Models: A Unified Approach, SAGE QASS series, 2000.

Publisher's Version

Datasets from the book: Capital Punishment, Scottish Vote, Educational Testing, World Copper Prices, Committee Bill Assignments
Incomplete Beta Function Table (Replication from Cox and Snell, 1968).
S-Plus/R code for the examples.
The Handout from my American Statistical Association (Boston chapter) Workshop. Contains lots of S-Plus/R code for GLMs.
Data from the Workshop (useful for running the examples).
Pat Altham's Homepage (several useful guides to GLMs in S-Plus and R).
Page for the Venables and Ripley book (includes GLM functions/code).
SAS whitepapers, including fitting GLMs in SAS.
Stata Help for GLMs.
GLMLAB: A Generalized Linear Model Package for MATLAB by Peter Dunn at the Department of Mathematics and Computing, University of Southern Queensland (Australia).
Check out Jim Lindsey's books on GLIM Code.
SAS Procs for running the book examples.