Preface
1. Introducing R and S-PLUS
S Basics
An Extended Illustration
S Functions for Basic Statistics
2. Reading and Manipulating Data
Data Input
Working with Data Frames
Matrices, Arrays, and Lists
Data Attributes, Modes, and Classes
3. Exploring and Transforming Data
Examining Distributions
Examining Relationships
Examining Multivariate Data
Transforming Data
4. Fitting Linear Models
Linear Least-Squares Regression
Dummy-Variable Regression
Analysis of Variance Models
User-Specified Contrasts*
General Linear Hypotheses*
Data and Confidence Ellipses
More on 1m and Model Formulas
5. Fitting Generalized Linear Models
The Structure of GLMs
Models for Categorical Responses
Poisson GLMs for Count Data
Odds and Ends
Fitting GLMs by Iterated Weighted Least-Squares*
6. Diagnosing Problems
Unusual Data
Non-Normal Errors
Non-Constant Error Variance
Nonlinearity
Collinearity and Variable Selection
Diagnostics for Generalized Linear Models
7. Drawing Graphs
A General Approach to S Graphics
Putting it Together
Effect Displays
Graphics Devices
8. Writing Programs
Defining Functions
Working With Matrices*
Program Control: Conditionals, Loops, and Recursion
Apply and its Relatives
Object-Oriented Programming in S*
Writing S Programs
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.
"The text does an outstanding job of providing the necessary
mechanics and theory of the S language. I will use this book in
every such course that I teach from this point on."
*Jeff Gill*
"The book provides a valuable supplement to texts on regression
analysis and linear models by showing readers how to put into
practice the strategies and techniques involved in modern
statistical methodology. It explains clearly the use of a very
sophisticated and powerful statistical software system. And, while
the examples and objectives are focused closely on regression and
related techniques, the discussion successfully conveys general
advice and principles for statistical computing with the S
system."
*William Jacoby*
"The style of presentation is rather informal and hands-on,
software usage is demonstrated using examples, without lengthy
discussions of theory...it is not necessary to switch to a more
theoretical text while reading it...In summary, I highly recommend
the book to anyone who wants to learn or teach applied regression
analysis with S."
*Friedrich Leisch*
"Together, John Fox′s Applied Regression Analysis, Linear Models
and Related Methods and the R and S-plus Companion to Applied
Regression have made a fantastic contribution to the world of
quantitative social science methology...For students and professors
that have yet to discover the wonders of the S language, the
Companion is a must read."
*The Political Methologist*
"The book is written in a lively style with an occasional witticism
interspresed. The writing is scholarly without being
stilted...Baker (2002) has said it nicely addressing the
combination of the Companion and the Fox (1997) statistical text.
He observed that Fox ′...has made a fantastic contribution to the
world of quantitative social science methodology′ (page 6). My
assessment exactly."
*Journal of Educational and Behavioral Sciences*
"This book is laid out in a way that facilitates its use in three
major applications...it is eminently practical...Overall, Fox has
created a remarkably useful book, not only for learning the S
language, but also for understanding applied regression techniques
as well."
*Canadian Journal of Sociology*
"[The book] provides an excellent vehicle for students and others
without previous experience with S in any form to become
comfortable with the basics of the enviornment and particularly
with the tools available for the preliminary exploratory analysis
and for fitting and evaluating linear and generalized linear
models...Fox makes thoughtful and effective efforts to prevent the
frustration that new users of sophisticated software all to often
experience."
*The American Statistician*
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