An R Companion to Applied Regression

An R Companion to Applied Regression

Second Edition

© 2011 | 472 pages | SAGE Publications, Inc


This is a broad introduction to the R statistical computing environment in the context of applied regression analysis. It is a thoroughly updated edition of John Fox's bestselling text An R and S-Plus Companion to Applied Regression (SAGE, 2002). The Second Edition is intended as a companion to any course on modern applied regression analysis.

The authors provide a step-by-step guide to using the high-quality free statistical software R, an emphasis on integrating statistical computing in R with the practice of data analysis, coverage of generalized linear models, enhanced coverage of R graphics and programming, and substantial web-based support materials.

An accompanying website for the book can be found at provides:

  • R scripts for examples by chapter
  • Data files used in the book
  • The car package (Companion to Applied Regression), an accompanying software for regression diagnostics and other regression-related tasks
  • Other resources to help students get the most out of the text
1. Getting Started With R
2. Reading and Manipulating Data
3. Exploring and Transforming Data
4. Fitting Linear Models
5. Fitting Generalized Linear Models
6. Diagnosing Problems in Linear and Generalized Linear Models
7. Drawing Graphs
8. Writing Programs
Author Index
Subject Index
Command Index
Data Set Index
Package Index
About the Authors

"The text is very clearly written. It contains much wisdom and useful hints for those trying to analyze data with R."

Robert W. Hayden

Used the Andy Field instead. But this is a very good book.

Myles Gartland
Management Dept, Rockhurst University
December 30, 2014

Good coverage of all types of regression, including error checking, and good examples in R are found throughout.

Mr Mark Van Ryzin
educational methodology, policy, and leadership, University Of Oregon
August 21, 2014

This is probably the best book on categorical and limited dependent variable models using R out there.

Professor Jun Xu
Sociology Dept, Ball State University
September 27, 2012

a) My teaching load was altered, and I no longer teach this class.

b) I suspect this text was too advanced for my graduate students in any case.

It's an excellent text, however, and I hold out hope of using it in a future advanced statistics course if I'm able to teach that at some point.

Dr Darrin Rogers
Psychology Anthropology Dept, University of Texas - Pan American
September 6, 2012
Key features

New to This Edition:

  • A second author, Sanford Weisberg, Professor of Statistics at the University of Minnesota, joins John Fox in this new edition.
  • A focus only on the R computing environment reflects the fact that open-source, free R has eclipsed its commercial cousin, S-PLUS.
  • New material on transformations, effects plots, and other new methodology has been added.
  • Many topics have been expanded, such as R graphics (Chapter 7) and R programming (Chapter 8).
  • The functions in the companion R car package have been expanded and revised to make them easier to use, more useful, and more consistent (this package is found on the accompanying website - see below).

Key Features:

  • Detailed worked-out examples introduce various facilities of R.
  • The book focuses on how to use R in everyday data analysis.
  • More demanding material is marked with an asterisk so that it may be skipped without loss of continuity.
  • An associated website at: includes several appendices for various extensions of regression analysis that are not covered in the text, downloadable scripts for all of the examples in the text, and more.


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ISBN: 9781412975148