Analyzing a Binary Response, Part 1: Introduction. Analyzing a Binary Response, Part 2: Regression Models. Analyzing a Multicategory Response. Analyzing a Count Response. Model Selection and Evaluation. Additional Topics. Appendices. Bibliography. Index.
Bilder, Christopher R.; Loughin, Thomas M.
"… I really enjoyed reading it due to its unique examples and
extensive R code...The book would be a great textbook for advanced
undergraduate or postgraduate courses, especially if training in R
programming is also a learning objective. A self-learner with basic
knowledge of categorical data analysis would find the book easy to
follow...Given the series of in-class videos provided on the
associated website and all the R code available online at
http://chrisbilder.com/categorical/, there is no doubt that this
book would be a great textbook. Personally I would like to
congratulate Bilder and Loughin on the writing of this valuable
book. Even before I had finished reading the book, I had already
recommended it to my students. Now, I highly recommend this book to
all readers."
— Australian & New Zealand Journal of Statistics, April 2016"This
book presents an extensive introduction to analysis of categorical
data with R. The context is relevant for a multitude of application
areas such as biology, ecology, medicine and sports, just to name a
few. Recent model-building techniques are covered...Throughout the
book, R is used not only as a data analysis tool but also as a
learning tool...The book takes an easy-to-understand approach by
partnering practical explanations with numerous illustrative
examples...To help students apply their knowledge, the book has
also provided an extensive number of exercises...The textbook can
also be a very useful reference."
— International Statistical Review, April 2016"In summary, I think
this book is well organized and nicely written. I really enjoyed
reading it, though I did not have time to run all of the R codes by
myself. I want to use this book as a textbook in a graduate course
for CDA. This book has many advantages. Compared to other standard
textbooks, its complete coverage of examples from many different
research areas and the R codes would let the students (and other
readers) become experts in CDA in all fields. Use of the same
examples throughout different chapters consistently provides
excellent process of data analysis. Furthermore, an extensive set
of exercises at the end of each chapter (over 65 pages in all) that
differ in scope and subject manner would be good supporting
materials for enhancing practical experiences of real data
analysis."
— Biometrics, 71, December 2015"… a valuable asset to any person
who wants to analyze categorical data. Bilder and Loughin demystify
categorical data analysis using a simple approach, with enough
statistical theory to allow the reader to understand the underlying
assumptions of the analyses involved, but with minimal,
unintimidating mathematical symbols, and equations. The authors
have managed to explain the statistics involved in categorical data
analysis in unadorned semantics and accompanied them with
corresponding R codes … . This is a major plus for this book.
Overall, the book is well written: It contains easy-to-follow R
codes, footnote explanations of material that could not be
explained within the text, and plenty of exercises at the end of
each chapter. … Excellent videos of Bilder teaching the material in
class, full R codes, and corresponding data, each arranged by
chapter, are available on a website. These resources make it easy
for readers to acquire a deeper understanding of categorical data
analysis. …
This book is a must-have tool for any biostatistician analyzing
categorical data in R. It could very well be used as a text in
intermediate-to-advanced applied courses in practical analysis of
categorical data."
— Biometrical Journal, 57, 2015"Bilder and Loughin have worked as a
dynamic duo for a number of years, and they clearly are blending
their knowledge, talents, experience, and teamwork to create this
valuable book. Analyzing categorical data correctly and in-depth is
not as simple as it appears in many courses and textbooks. As a
result, many people can get the wrong idea about what could and
should be done with categorical data, and hence their results can
be inconclusive or incorrect. This book gives users the full scoop
when it comes to analyzing categorical data of all types, and it
does so in an easy-to-understand way, giving confidence to the
reader to go ahead and apply the ideas in practice. The use of R
for analyzing data is becoming a worldwide phenomenon and a staple
for data analysts on every level. As its popularity grows, it
becomes critical for beginners to become comfortable with
understanding and using R to analyze their data. Through the
special attention paid to teaching the basics of R, as well as
providing step-by-step particulars in using R in each separate
analysis, Bilder and Loughin help establish and promote a group of
confident, comfortable users of this software that can seem a
mystery to many. I highly and happily recommend this book to anyone
who plans to analyze categorical data in their careers—which
includes most all of us!"
— Deborah J. Rumsey, PhD, Auxiliary Professor and Statistics
Education Specialist, Department of Statistics, The Ohio State
University
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