Logistic Regression A Self-Learning Text
This very popular textbook is now in its third edition. Whether students or working professionals, readers appreciate its unique "lecture book" format. They often say the book reads like they are listening to an outstanding lecturer. This edition includes
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David G. Kleinbaum · Mitchel Klein
Logistic Regression A Self-Learning Text Third Edition
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Statistics for Biology and Health Series Editors M. Gail, K. Krickeberg, J.M. Samet, A. Tsiatis, W. Wong
For other titles published in this series, go to http://www.springer.com/series/2848
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David G. Kleinbaum
Mitchel Klein
Logistic Regression A Self‐Learning Text Third Edition
With Contributions by Erica Rihl Pryor
David G. Kleinbaum Mitchel Klein Department of Epidemiology Emory University Rollins School of Public Health Atlanta, GA 30322 USA [email protected] [email protected] Series Editors M. Gail National Cancer Institute Rockville, MD 20892 USA
K. Krickeberg Le Chatelet F-63270 Manglieu France
A. Tsiatis Department of Statistics North Carolina State University Raleigh, NC 27695 USA
W. Wong Department of Statistics Stanford University Stanford, CA 94305-4065 USA
Jonathan M. Samet Department of Preventive Medicine Keck School of Medicine University of Southern California Los Angeles, CA 90089 USA
ISBN: 978-1-4419-1741-6 e-ISBN: 978-1-4419-1742-3 DOI 10.1007/978-1-4419-1742-3 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2009943538 # Springer Science+Business Media LLC 2010 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper
Springer is part of Springer Science+Business Media (www.springer.com)
To Edna Kleinbaum and Rebecca Klein
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Contents Preface
xiii
Acknowledgements
Chapter 1
xvii
Introduction to Logistic Regression Introduction 2 Abbreviated Outline 2 Objectives 3 Presentation 4 Detailed Outline 29 Key Formulae 32 Practice Exercises 32 Test 34 Answers to Practice Exercises
Chapter 2
71
Computing the Odds Ratio in Logistic Regression 73 Introduction 74 Abbreviated Outline 74 Objectives 75 Presentation 76 Detailed Outline 92 Practice Exercises 96 Test 98 Answers to Practice Exercises
Chapter 4
37
Important Special Cases of the Logistic Model 41 Introduction 42 Abbreviated Outline 42 Objectives 43 Presentation 45 Detailed Outline 65 Practice Exercises 67 Test 69 Answers to Practice Exercises
Chapter 3
1
101
Maximum Likelihood Techniques: An Overview 103 Introduction 104 Abbreviated Outline
104 vii
viii
Contents Objectives 105 Presentation 106 Detailed Outline 122 Practice Exercises 124 Test 124 Answers to Practice Exercises
Chapter 5
Stat
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