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Generalized Linear Models

Jeff Gill | Michelle Torres
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A01=Jeff Gill
A01=Jefferson M. Gill
A01=Michelle Torres
A01=Silvia Michelle Torres Pacheco
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Generalized linear models
Generalized Linear Models: A Unified Approach
Gill
Language_English
Linear models
PA=Available
Price_€20 to €50
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QASS
Quantitative Applications in the Social Sciences
Second Edition
SN=Quantitative Applications in the Social Sciences
softlaunch

Product details

  • ISBN 9781506387345
  • Weight: 230g
  • Dimensions: 139 x 215mm
  • Publication Date: 11 Jul 2019
  • Publisher: SAGE Publications Inc
  • Publication City/Country: US
  • Product Form: Paperback
  • Language: English
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Description

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&
About Jeff Gill | Jefferson M. Gill | Michelle Torres | Silvia Michelle Torres Pacheco
Jeff Gill is a Distinguished Professor of Government, a Professor of Statistics, and a Member of the Center for Behavioral Neuroscience at American University. His research applies Bayesian modeling and data analysis (decision theory, testing, model selection, elicited priors) to questions in general social science quantitative methodology, political behavior and institutions, medical/health data analysis especially physiology, circulation/blood, pediatric traumatic brain injury, and epidemiological measurement/data issues, using computationally intensive tools (Monte Carlo methods, MCMC, stochastic optimization, nonparametrics). Michelle Torres is Assistant professor in the Department of Political Science at Rice University. She holds a PhD in Political Science and a AM in Statistics from Washington University in St. Louis. Her research interests are in the fields of political methodology, with a special focus on survey methodology, computer vision, causal inference, public opinion, and political communication.

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