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A01=Jefferson M. Gill
A01=Silvia Michelle Torres Pacheco
Age Group_Uncategorized
Age Group_Uncategorized
Author_Jefferson M. Gill
Author_Silvia Michelle Torres Pacheco
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Generalized Linear Models: A Unified Approach

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&


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A01=Jefferson M. GillA01=Silvia Michelle Torres PachecoAge Group_UncategorizedAuthor_Jefferson M. GillAuthor_Silvia Michelle Torres Pachecoautomatic-updateCategory1=Non-FictionCategory=GPSCategory=JHBCCategory=JPACategory=PBTCategory=PBWCOP=United StatesDelivery_Delivery within 10-20 working daysLanguage_EnglishPA=AvailablePrice_€20 to €50PS=ActiveSN=Quantitative Applications in the Social Sciencessoftlaunch
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Product Details
  • Weight: 230g
  • Dimensions: 139 x 215mm
  • Publication Date: 11 Jul 2019
  • Publisher: SAGE Publications Inc
  • Publication City/Country: United States
  • Language: English
  • ISBN13: 9781506387345

About Jefferson M. GillSilvia 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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