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Applied Regression Analysis and Generalized Linear Models

English

By (author): John Fox

Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book. 

Accompanying website resources containing all answers to the end-of-chapter exercises. Answers to odd-numbered questions, as well as datasets and other student resources are available on the authors website.

NEW! Bonus chapter on Bayesian Estimation of Regression Models also available at the authors website. See more
Current price €149.39
Original price €165.99
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Product Details
  • Weight: 1690g
  • Dimensions: 177 x 254mm
  • Publication Date: 26 May 2015
  • Publisher: SAGE Publications Inc
  • Publication City/Country: United States
  • Language: English
  • ISBN13: 9781452205663

About John Fox

John Fox received a BA from the City College of New York and a PhD from the University of Michigan both in Sociology. He is Professor Emeritus of Sociology at McMaster University in Hamilton Ontario Canada where he was previously the Senator William McMaster Professor of Social Statistics. Prior to coming to McMaster he was Professor of Sociology Professor of Mathematics and Statistics and Coordinator of the Statistical Consulting Service at York University in Toronto. Professor Fox is the author of many articles and books on applied statistics including emph{Applied Regression Analysis and Generalized Linear Models Third Edition} (Sage 2016). He is an elected member of the R Foundation an associate editor of the Journal of Statistical Software a prior editor of R News and its successor the R Journal and a prior editor of the Sage Quantitative Applications in the Social Sciences monograph series.  

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