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Applied Regression Analysis, Linear Models, and Related Methods

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Author: John Fox
Publisher: Sage Publications, Inc
Category: Book

List Price: ~~$115.00~~
Buy New: $92.00
You Save: $23.00 (20%)

New (9) Used (9) from $69.95

Media: Hardcover
Number Of Items: 1
Pages: 624
Shipping Weight (lbs): 2.7
Dimensions (in): 10.1 x 7.2 x 1.5

ISBN: 080394540X
Dewey Decimal Number: 300.01519536
EAN: 9780803945401
ASIN: 080394540X

Publication Date: February 5, 1997
Availability: Usually ships in 2 to 3 weeks

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Editorial Reviews:

Product Description
p"I have never read a book on regression that reflects as broad and profound a grasp of the concepts of statistics as this book does. In every topic John Fox deals with--and he does not avoid the slippery ones--he shows a clarity and depth of understanding that goes beyond anything else I have seen in textbooks and that matches the works of the leading researchers within each field."/p p --Georges Monette, Department of Mathematics and Statistics, York University /p p"The selection of examples throughout the book is one of its strengths, as they are generally quite engaging in ''real-world'' interest, and demonstrate the practical use (and limitations) of the statistical methods far better than contrived data. I appreciate the fact that John Fox describes what each example ''means'' in terms of the substantive problem behind the data--students would find this quite useful."/p p --Michael Friendly, Psychology Department, York University /p pAimed at researchers and students who want to use linear models for data analysis, John Fox's book provides an accessible, in-depth treatment of regression analysis, linear models, and closely related methods. Fox incorporates nearly 200 graphs and numerous examples and exercises that employ real data from the social sciences. He begins the book with a concise consideration of the role of statistical data analysis in social research. He next covers graphical methods for examining and transforming data, linear least-squares regression, dummy-variables regression, and analysis of variance. Fox also explores diagnostic methods for discovering whether a linear model fit to data adequately represents the data; extensions to linear least squares, including logit and probit models, time-series regression, nonlinear regression, robust regression, and nonparametric regression; and empirical methods for assessing sampling variation, including the bootstrap and cross-validation. More difficult material is segregated in separate sections and chapters and several appendixes are also included presenting background information. Scholars, professionals, researchers, and students in research methods, evaluation, education, sociology, and psychology will appreciate the enhanced and thorough treatment that regression analysis, linear models, and other related methods have received by author John Fox. /p

Customer Reviews: Read 2 more reviews...

5 out of 5 stars

Useful and understandable February 19, 2007
1 out of 1 found this review helpful

This book takes an unusual start. It begin with the assumption that regression usually has to the data and illustrates how the assumption can be violated, illustrates why graphical analysis is important for data analysis and, in chapter 4, explains how to "fix" the violations of the requirement to the data, before actually starting to explain regression models. I find this unusual approach very insightful. Moreover, difficult parts are marked with an asterisk and can be left out if this is more convenient for the reader.br /br /Although some math is required, I find this book very understandable throughout due to its focus on application. The book covers linear models and some extensions (for the large part of the book) and also Logit- and Probit models for nominal data (in Chapter 15). Chapter 16 deals with bootstrapping, and the appendices give some introduction to statistical and mathematical requirements that the book poses.br /br /Overall, a good buy for people who apply regressions (as the title says), probably not so much for those who are in statistics, math, or econ.

1 out of 5 stars

Not suitable as an introduction to regression analysis March 8, 2006
1 out of 3 found this review helpful

While this book is no doubt useful to students with a solid background in math and statistics, I certainly would NOT recommend it as an introduction to regression analysis. The explanations tend to be far too complex and inaccessible for most graduate students in the social sciences. Put it this way: after having spent almost $100 on this book, I've had more success finding useful explanations of some of the book's topics on Google than I have had by reading the book itself.

3 out of 5 stars

Useful but disorganized February 15, 2006
2 out of 2 found this review helpful

This book is a useful first book in linear regression. Fox covers the basics effectively, and the book nicely complements Fox's guide to Regression in R and S Plus. br /br /My biggest problem with the book is Fox's meandering prose style. Few of his paragraphs start with topic sentences, and the formatting of the text means it's almost impossible to figure out what the take-away points are. (It would have been nice for Fox to reverse-engineer his chapters from the end-of-chapter summaries, which are the most helpful guide to his book, and actually happen to be organized.br /br /For a more organized and more clearly written guide to regression, see Basic Econometrics by Gujarati.br /br /

4 out of 5 stars

Good but Flawed May 19, 2005
4 out of 4 found this review helpful

Dr. Fox has written in a thoughtful original manner. Example, pretty much all regression books starts out with a graph of simple linear regression model statisfying all the strong assumptions that went into it. Dr. Fox starts out by showing graph of data that violates every single assumption. This is the sort of innovative and creative approach that shows what is best about this book. Dr. Fox has a deep conceptual understanding of this material.br /br /The book doesn't get 5 stars becuase a significant flaw. Dr. Fox (or perhaps the publishers) wanted every kind of student to be able to read this book. Both students with advanced and also students with no statistical/mathematical expertise and sophistication. The result is a fragmented text. For instance, the geometrical interpretation of least squares fit is not integrated into the initial discussion (it comes 130 pages later!). If it was integrated then many of the derivations and discussions would be far simpler and intuitive. This sepration allows a student with no linear algebra background to read this text but it also wastes the time of the advanced students who have to wait for the more simpler and intuitive approach.

5 out of 5 stars

Get it now!!! Best on the subject. January 16, 2004
4 out of 4 found this review helpful

Dr. Fox makes an excellent contribution to the student community across geographies. The text is an excellent balance between theory and practical applications of the linear regression methodology. The author is extremely clear in explaining not only simple and multiple linear regression, but also topics such as bootstraping, logistic and other regression techniques for non normal response variables. The book do not fall down near your toes: the topics are covered in a depth that is amenable for a PhD student.brIt is very interesting also to look at the many side comments and suggested readings that the author introduces many times in the book. I congratulate Dr. Fox for this clear, understandable and easy to follow text.

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