Categorical data arise often in many fields, including biometrics,
economics, management, manufacturing, marketing, psychology, and
sociology. This book provides an introduction to the analysis of
such data. The coverage is broad, using the loglinear Poisson
regression model and logistic binomial regression models as the
primary engines for methodology. Topics covered include count
regression models, such as Poisson, negative binomial,
zero-inflated, and zero-truncated models; loglinear models for
two-dimensional and multidimensional contingency tables, including
for square tables and tables with ordered categories; and
regression models for two-category (binary) and multiple-category
target variables, such as logistic and proportional odds models.
All methods are illustrated with analyses of real data examples,
many from recent subject area journal articles. These analyses are
highlighted in the text, and are more detailed than is typical,
providing discussion of the context and background of the problem,
model checking, and scientific implications. More than 200
exercises are provided, many also based on recent subject area
literature. Data sets and computer code are available at a web site
devoted to the text. Adopters of this book may request a solutions
manual from:
[email protected]. From the reviews: "Jeff
Simonoff's book is at the top of the heap of categorical data
analysis textbooks...The examples are superb. Student reactions in
a class I taught from this text were uniformly positive,
particularly because of the examples and exercises. Additional
materials related to the book, particularly code for S-Plus, SAS,
and R, useful for analysis of examples, can be found at the
author's Web site at New York University. I liked this book for
this reason, and recommend it to you for pedagogical purposes."
(Stanley Wasserman, The American Statistician, August 2006, Vol.
60, No. 3) "The book has various noteworthy features. The examples
used are from a variety of topics, including medicine, economics,
sports, mining, weather, as well as social aspects like
needle-exchange programs. The examples motivate the theory and also
illustrate nuances of data analytical procedures. The book also
incorporates several newer methods for analyzing categorical data,
including zero-inflated Poisson models, robust analysis of binomial
and poisson models, sandwich estimators, multinomial smoothing,
ordinal agreement tables...this is definitely a good reference book
for any researcher working with categorical data." Technometrics,
May 2004 "This guide provides a practical approach to the
appropriate analysis of categorical data and would be a suitable
purchase for individuals with varying levels of statistical
understanding." Paediatric and Perinatal Epidemiology, 2004, 18
"This book gives a fresh approach to the topic of categorical data
analysis. The presentation of the statistical methods exploits the
connection to regression modeling with a focus on practical
features rather than formal theory...There is much to learn from
this book. Aside from the ordinary materials such as association
diagrams, Mantel-Haenszel estimators, or overdispersion, the reader
will also find some less-often presented but interesting and
stimulating topics...[T]his is an excellent book, giving an
up-to-date introduction to the wide field of analyzing categorical
data." Biometrics, September 2004 "...It is of great help to data
analysts, practitioners and researchers who deal with categorical
data and need to get a necessary insight into the methods of
analysis as well as practical guidelines for solving problems."
International Journal of General Systems, August 2004 "The author
has succeeded in writing a useful and readable textbook combining
most of general theory and practice of count data." Kwantitatieve
Methoden "The book especially stresses how to analyze and interpret
data...In fact, the highly detailed multi-page descriptions of
analysis and interpretation make the book stand out." Mathematical
Geology, February 2005 "Overall, this is a competent and detailed
text that I would recommend to anyone dealing with the analysis of
categorical data." Journal of the Royal Statistical Society "This
important work allows for clear analogies between the well-known
linear models for Gaussian data and categorical data problems. ...
Jeffrey Simonoff's Analyzing Categorical Data provides an
introduction to many of the important ideas and methods for
understanding counted data and tables of counts. ... Some readers
will find Simonoff's style very much to their liking due to
reliance on extended real data examples to illuminate ideas. ... I
think the extensive examples will appeal to most students."
(Sanford Weisberg, SIAM Review, Vol. 47 (4), 2005) "It is clear
that the focus of Simonoff's book is different from other books on
categorical data analysis. ... As an introductory textbook, the
book is comprehensive enough since all basic topics in categorical
data analysis are discussed. ... I think Simonoff's book is a
valuable addition to the literature because it discusses important
models for counts ... ." (Jeroen K. Vermunt, Statistics in
Medicine, Vol. 24, 2005) "The author based this book on his notes
for a class with a very diverse pool of students. The material is
presented in such a way that a very heterogeneous group of students
could grasp it. All methods are illustrated with analyses of real
data examples. The author provides a detailed discussion of the
context and background of the problem. ... The book is very
interesting and can be warmly recommended to people working with
categorical data." (EMS - European Mathematical Society Newsletter,
December, 2004) "Categorical data arise often in many fields ... .
This book provides an introduction to the analysis of such data.
... All methods are illustrated with analyses of real data
examples, many from recent subject-area journal articles. These
analyses are highlighted in the text and are more detailed than is
typical ... . More than 200 exercises are provided, including many
based on recent subject-area literature. Data sets and computer
code are available at a Web site devoted to this text." (T.
Postelnicu, Zentralblatt MATH, Vol. 1028, 2003) "This book grew out
of notes prepared by the author for classes in categorical data
analysis. The presentation is fresh and compelling to read.
Regression ideas are used to motivate the modelling presented. The
book focuses on applying methods to real problems; many of these
will be novel to readers of statistics texts ... . All chapters end
with a section providing references to books or articles for the
inquiring reader." (C.M. O'Brien, Short Book Reviews, Vol. 23 (3),
2003)
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