Applied Regression Analysis and Generalized Linear Models,3rd.pdf

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APPLIED REGRESSION ANALYSIS AND GENERALIZED LINEAR MODELS-FRONT COVER

APPLIED REGRESSION ANALYSIS AND GENERALIZED LINEAR MODELS

BRIEF CONTENTS

CONTENTS

PREFACE

ABOUT THE AUTHOR

CHAPTER 1- STATISTICAL MODELS AND SOCIAL SCIENCE

PART I- DATA CRAFT

CHAPTER 2- WHAT IS REGRESSION ANALYSIS?

CHAPTER 3- EXAMINING DATA

CHAPTER 4- TRANSFORMING DATA

PART II- LINEAR MODELS AND LEAST SQUARES

CHAPTER 5- LINEAR LEAST-SQUARES REGRESSION

CHAPTER 6- STATISTICAL INFERENCE FOR REGRESSION

CHAPTER 7- DUMMY-VARIABLE REGRESSION

CHAPTER 8- ANALYSIS OF VARIANCE

CHAPTER 9- STATISTICAL THEORY FOR LINEAR MODELS

CHAPTER 10- THE VECTOR GEOMETRY OF LINEAR MODELS

PART III- LINEAR-MODEL DIAGNOSTICS

CHAPTER 11- UNUSUAL AND INFLUENTIAL DATA

CHAPTER 12- DIAGNOSING NON-NORMALITY, NONCONSTANT ERROR VARIANCE, AND NONLINEARITY

CHAPTER 13- COLLINEARITY AND ITS PURPORTED REMEDIES

PART IV- GENERALIZED LINEAR MODELS

CHAPTER 14- LOGIT AND PROBIT MODELS FOR CATEGORICAL RESPONSE VARIABLES

CHAPTER 15- GENERALIZED LINEAR MODELS

PART V- EXTENDING LINEAR AND GENERALIZED LINEAR MODELS

CHAPTER 16- TIME-SERIES REGRESSION AND GENERALIZED LEAST SQUARES

CHAPTER 17- NONLINEAR REGRESSION

CHAPTER 18- NONPARAMETRIC REGRESSION

CHAPTER 19- ROBUST REGRESSION

CHAPTER 20- MISSING DATA IN REGRESSION MODELS

CHAPTER 21- BOOTSTRAPPING REGRESSION MODELS

CHAPTER 22- MODEL SELECTION, AVERAGING, AND VALIDATION

PART VI- MIXED-EFFECTS MODELS

CHAPTER 23- LINEAR MIXED-EFFECTS MODELS FOR HIERARCHICAL AND LONGITUDINAL DATA

CHAPTER 24- GENERALIZED LINEAR AND NONLINEAR MIXED-EFFECTS MODELS

APPENDIX A

REFERENCES

AUTHOR INDEX

SUBJECT INDEX

DATA SET INDEX

THIRD EDITION APPLIED REGRESSION ANALYSIS and GENERALIZED LINEAR MODELS

For Bonnie and Jesse (yet again)

THIRD EDITION APPLIED REGRESSION ANALYSIS and GENERALIZED LINEAR MODELS John Fox McMaster University

FOR INFORMATION: Copyright © 2016 by SAGE Publications, Inc. SAGE Publications, Inc. 2455 Teller Road Thousand Oaks, California 91320 E-mail: order@sagepub.com SAGE Publications Ltd. 1 Oliver’s Yard 55 City Road London EC1Y 1SP United Kingdom SAGE Publications India Pvt. Ltd. B 1/I 1 Mohan Cooperative Industrial Area Mathura Road, New Delhi 110 044 India SAGE Publications Asia-Pacific Pte. Ltd. 3 Church Street #10–04 Samsung Hub Singapore 049483 Acquisitions Editor: Vicki Knight Associate Digital Content Editor: Katie Bierach Editorial Assistant: Yvonne McDuffee Production Editor: Kelly DeRosa Copy Editor: Gillian Dickens Typesetter: C&M Digitals (P) Ltd. Proofreader: Jennifer Grubba Cover Designer: Anupama Krishnan Marketing Manager: Nicole Elliott All rights reserved. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without permission in writing from the publisher. Cataloging-in-Publication Data is available for this title from the Library of Congress. ISBN 978-1-4522-0566-3 Printed in the United States of America 15 16 17 18 19 10 9 8 7 6 5 4 3 2 1

Brief Contents _____________ Preface About the Author 1. Statistical Models and Social Science I. DATA CRAFT 2. What Is Regression Analysis? 3. Examining Data 4. Transforming Data II. LINEAR MODELS AND LEAST SQUARES 5. Linear Least-Squares Regression 6. Statistical Inference for Regression 7. Dummy-Variable Regression 8. Analysis of Variance 9. Statistical Theory for Linear Models* 10. The Vector Geometry of Linear Models* III. LINEAR-MODEL DIAGNOSTICS 11. Unusual and Influential Data 12. Diagnosing Non-Normality, Nonconstant Error Variance, and Nonlinearity 13. Collinearity and Its Purported Remedies IV. GENERALIZED LINEAR MODELS 14. Logit and Probit Models for Categorical Response Variables 15. Generalized Linear Models xv xxiv 1 12 13 28 55 81 82 106 128 153 202 245 265 266 296 341 369 370 418

V. EXTENDING LINEAR AND GENERALIZED LINEAR MODELS 16. Time-Series Regression and Generalized Least Squares* 17. Nonlinear Regression 18. Nonparametric Regression 19. Robust Regression* 20. Missing Data in Regression Models 21. Bootstrapping Regression Models 22. Model Selection, Averaging, and Validation VI. MIXED-EFFECTS MODELS 23. Linear Mixed-Effects Models for Hierarchical and Longitudinal Data 24. Generalized Linear and Nonlinear Mixed-Effects Models Appendix A References Author Index Subject Index Data Set Index 473 474 502 528 586 605 647 669 699 700 743 759 762 773 777 791

Contents _________________ Preface About the Author 1. Statistical Models and Social Science 1.1 Statistical Models and Social Reality 1.2 Observation and Experiment 1.3 Populations and Samples Exercise Summary Recommended Reading I. DATA CRAFT 2. What Is Regression Analysis? 2.1 Preliminaries 2.2 Naive Nonparametric Regression 2.3 Local Averaging Exercise Summary 3. Examining Data 3.1 Univariate Displays 3.1.1 Histograms 3.1.2 Nonparametric Density Estimation 3.1.3 Quantile-Comparison Plots 3.1.4 Boxplots 3.2 Plotting Bivariate Data 3.3 Plotting Multivariate Data 3.3.1 Scatterplot Matrices 3.3.2 Coded Scatterplots 3.3.3 Three-Dimensional Scatterplots 3.3.4 Conditioning Plots Exercises Summary Recommended Reading 4. Transforming Data 4.1 The Family of Powers and Roots 4.2 Transforming Skewness 4.3 Transforming Nonlinearity xv xxiv 1 1 4 8 10 10 11 12 13 15 18 22 25 26 28 30 30 33 37 41 44 47 48 50 50 51 53 53 54 55 55 59 63

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