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Applied Regression Analysis and Generalized Linear Models

Applied Regression Analysis and Generalized Linear Models

Applied Regression Analysis and Generalized Linear Models Hardback - 2008

by John Fox

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Description

SAGE Publications, Incorporated, 2008. Hardcover. Very Good. Disclaimer:A copy that has been read, but remains in excellent condition. Pages are intact and are not marred by notes or highlighting, but may contain a neat previous owner name. The spine remains undamaged. At ThriftBooks, our motto is: Read More, Spend Less.Dust jacket quality is not guaranteed.
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Details

  • Title Applied Regression Analysis and Generalized Linear Models
  • Author John Fox
  • Binding Hardback
  • Edition [ Edition: secon
  • Condition Used - Very good
  • Pages 688
  • Volumes 1
  • Language ENG
  • Publisher SAGE Publications, Incorporated, Thousand Oaks, California, U.S.A.
  • Publication date 2008
  • Illustrated Yes
  • Bookseller's Inventory # G0761930426I4N00
  • ISBN 9780761930426 / 0761930426
  • Weight 3 lbs (1.36 kg)
  • Dimensions 10 x 7 x 1.61 in (25.40 x 17.78 x 4.09 cm)
  • Category Sociology
  • Library of Congress subjects Social sciences - Statistical methods, Regression analysis
  • Library of Congress Catalogue Number 2007047617
  • Dewey Decimal Code 300.151
  • Quantity available 1

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From the publisher


Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Second Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material throughout the book.

Key Updates to the Second Edition

  • Provides greatly enhanced coverage of generalized linear models, with an emphasis on models for categorical and count data
  • Offers new chapters on missing data in regression models and on methods of model selection
  • Includes expanded treatment of robust regression, time-series regression, nonlinear regression, and nonparametric regression
  • Incorporates new examples using larger data sets
  • Includes an extensive Web site at http: //www.sagepub.com/fox that presents appendixes, data sets used in the book and for data-analytic exercises, and the data-analytic exercises themselves

Intended Audience:
This core text will be a valuable resource for graduate students and researchers in the social sciences (particularly sociology, political science, and psychology) and other disciplines that employ linear and related models for data analysis.

About the author

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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