Applied Regression Analysis and Generalized Linear Models / Edition 2

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Overview

Linear models, their variants, and extensions are among the most useful and widely used statistical tools for social research. The Second Edition of Applied Regression Analysis and Generalized Linear Models provides an accessible, in-depth, modern treatment of regression analysis, linear models, and closely related methods.

Author John Fox makes the text as user-friendly as possible: With the exception of three chapters, several sections, and a few shorter passages, the prerequisite for reading the book is a course in basic applied statistics that covers the elements of statistical data analysis and inference. Even relatively advanced topics (such as methods for handling missing data and bootstrapping) are presented in a manner consistent with this prerequisite.

Key Features of the Second Edition

  • Covers regression models--such as generalized linear models, limited-dependent-variable-models, mixed models and Cox regression--and methods that are increasingly being used in social science research
  • Contains a more robust Web site with extensive appendices of background material (matrices, linear algebra, vector geometry; calculus; probability and estimation); data sets used in the book and for data analytic exercises; and the data-analytic exercises themselves.
  • Incorporates real data from the social sciences that is similar to data readers are likely to encounter.

This book should be of interest to students and researchers in the social sciences, as well as other disciplines that employ linear models for data analysis, and in courses on applied regression and linear models where the subject matter ofapplications is not of special concern.

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Editorial Reviews

The Political Methodologist
"helps to bridge the divide between introductory and intermediate to advanced methods courses. The book is written in a clear, concise manner and organized in such a way as to help facilitate comprehension of the material...Together [with] theR and S-plus Companion to Applied Regression [has] made a fantastic contribution to the world of quantitative social science methology. "— Ryan Baker
Joseph Cavanaugh
"This is an excellent text on regression applications and methods, written with authority, lucidity, and eloquence. "
The Political Methodologist - Ryan Baker
"helps to bridge the divide between introductory and intermediate to advanced methods courses. The book is written in a clear, concise manner and organized in such a way as to help facilitate comprehension of the material...Together [with] theR and S-plus Companion to Applied Regression [has] made a fantastic contribution to the world of quantitative social science methology."
E. C. Hedberg
The strength of this text is the unified presentation of several regression topics that provides the student with a global perspective on regression analysis. The student is well served with this unified approach as it facilitates deeper research on any one topic with more advanced texts.
Corey S. Sparks
This text is a one-stop shop for me for my first year stats sequence for students in our program. Those wanting the technical detail will be satisfied; those wanting an excellent explanation of these methods using real-world examples and approachable language will also be satisfied.
Michael S. Lynch
I have enjoyed using previous editions of this text and look forward to using this edition. It covers all key topics, and quite a few advanced ones, in one well-written text.
Journal of the American Statistical Association (review of the second edition)
PRAISE FOR THE PREVIOUS EDITIONS

In summary, this is an excellent text on regression applications and methods, written with authority, lucidity, and eloquence. The second edition provides substantive and topical updates, and makes the book suitable for courses designed to emphasize both the classical and the modern aspects of regression.

Journal of the American Statistical Association (review of the first edition)
PRAISE FOR THE PREVIOUS EDITIONS

Even though the book is written with social scientists as the target audience, the depth of material and how it is conveyed give it far broader appeal. Indeed, I recommend it as a useful learning text and resource for researchers and students in any field that applies regression or linear models (that is, most everyone), including courses for undergraduate statistics majors…. The author is to be commended for giving us this book, which I trust will find a wide and enduring readership.

Chance (review of the first edition)
PRAISE FOR THE PREVIOUS EDITIONS

[T]his wonderfully comprehensive book focuses on regression analysis and linear models… We enthusiastically recommend this book—having used it in class, we know that it is thorough and well-liked by students.

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Product Details

  • ISBN-13: 9780761930426
  • Publisher: SAGE Publications
  • Publication date: 4/16/2008
  • Edition description: Second Edition
  • Edition number: 2
  • Pages: 688
  • Sales rank: 236,504
  • Product dimensions: 7.10 (w) x 10.10 (h) x 1.70 (d)

Meet the Author

John Fox is professor of sociology at Mc Master University in Hamilton, Ontario, Canada. Fox earned a Ph D in sociology from the University of Michigan in 1972, and prior to arriving at Mc Master, he taught at the University of Alberta and at York University in Toronto, where he was cross-appointed in the sociology and mathematics and statistics departments and directed the university's statistical consulting service. He has delivered numerous lectures and workshops on statistical topics in North and South America, Europe, and Asia, at such places as the summer program of the Inter-University Consortium for Political and Social Research, the Oxford University Spring School in Quantitative Methods for Social Research, and the annual meetings of the American Sociological Association. Much of his recent work has been on formulating methods for visualizing complex statistical models and on developing software in the R statistical computing environment. He is the author and co-author of many articles, in such journals as Sociological Methodology, Sociological Methods and Research, The Journal of the American Statistical Association, The Journal of Statistical Software, The Journal of Computational and Graphical Statistics, Statistical Science, Social Psychology Quarterly, The Canadian Review of Sociology and Anthropology, and The Canadian Journal of Sociology. He has written a number of other books, including Regression Diagnostics (SAGE, 1991), Nonparametric Simple Regression (SAGE, 2000), Multiple and General-ized Nonparametric Regression (SAGE, 2000), A Mathematical Primer for Social Statistics (SAGE, 2008), and, with Sanford Weisberg, An R Companion to Applied Regression, Second Edition (SAGE, 2010). Fox also edits the SAGE Quantitative Applications in the Social Sciences (QASS) monograph series.

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Table of Contents

1 Statistical Models and Social Science 1

Pt. I Data Craft 11

2 What Is Regression Analysis? 13

3 Examining Data 26

4 Transforming Data 50

Pt. II Linear Models and Least Squares 75

5 Linear Least-Squares Regression 77

6 Statistical Inference for Regression 100

7 Dummy-Variable Regression 120

8 Analysis of Variance 143

9 Statistical Theory for Linear Models 187

10 The Vector Geometry of Linear Models 220

Pt. III Linear-Model Diagnostics 239

11 Unusual and Influential Data 241

12 Diagnosing Non-Normality, Nonconstant Error Variance, and Nonlinearity 267

13 Collinearity and Its Purported Remedies 307

Pt. IV Generalized Linear Models 333

14 Logit and Probit Models for Categorical Response Variables 335

15 Generalized Linear Models 279

Pt. V Extending Linear and Generalized Linear Models 425

16 Time-Series Regression and Generalized Least Squares 427

17 Nonlinear Regression 451

18 Nonparametric Regression 476

19 Robust Regression 530

20 Missing Data in Regression Models 548

21 Bootstrapping Regression Models 587

22 Model Selection, Averaging, and Validation 607

App. A Notation 636

References 638

Author Index 648

Subject Index 652

Data Set Index 664

About the Author 665

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