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Logistic Regression: A Self-Learning Text, 2nd Edition

Authors: David G. Kleinbaum and Mitchel Klein
Publisher: Springer
Copyright: 2002
ISBN-10: 0-387-95397-3
ISBN-13: 978-0-387-95397-7
Pages: 513; hardcover
Price: $69.00
Supplements: datasets

Comment from the Stata technical group

This book, the second edition of the 1994 text, succeeds in demonstrating that one need not be a mathematician to fully understand the underpinnings of logistic regression in all its forms. Ideally suited for a graduate course for students in the medical sciences, the text has the look and feel of a course textbook, with formulas, diagrams, and important points set off in the side margins for emphasis. Also, each chapter contains a summary, detailed outline, practice exercises (with answers), and chapter test.

The mathematics is kept to the most basic level, but nevertheless, because of its completeness in coverage of logistic regression, this text would be a good reference for even the most theoretical statistician. In fact, those already well versed in logistic regression methods will benefit from seeing advanced topics such as generalized estimating equations (GEE) explained from first principles.


Table of contents

Preface
Acknowledgments
Chapter 1 Introduction to Logistic Regression
Introduction
Abbreviated Outline
Objectives
Presentation
Detailed Outline
Key Formulae
Practice Exercises
Test
Answers to Practice Exercises
Chapter 2 Important Special Cases of the Logistic Model
Introduction
Abbreviated Outline
Objectives
Presentation
Detailed Outline
Practice Exercises
Test
Answers to Practice Exercises
Chapter 3 Computing the Odds Ratio in Logistic Regression
Introduction
Abbreviated Outline
Objectives
Presentation
Detailed Outline
Practice Exercises
Test
Answers to Practice Exercises
Chapter 4 Maximum Likelihood Techniques: An Overview
Introduction
Abbreviated Outline
Objectives
Presentation
Detailed Outline
Practice Exercises
Test
Answers to Practice Exercises
Chapter 5 Statistical Inferences Using Maximum Likelihood Techniques
Introduction
Abbreviated Outline
Objectives
Presentation
Detailed Outline
Practice Exercises
Test
Answers to Practice Exercises
Chapter 6 Modeling Strategy Guidelines
Introduction
Abbreviated Outline
Objectives
Presentation
Detailed Outline
Practice Exercises
Test
Answers to Practice Exercises
Chapter 7 Modeling Strategy for Assessing Interaction and Confounding
Introduction
Abbreviated Outline
Objectives
Presentation
Detailed Outline
Practice Exercises
Test
Answers to Practice Exercises
Chapter 8 Analysis of Matched Data Using Logistic Regression
Introduction
Abbreviated Outline
Objectives
Presentation
Detailed Outline
Practice Exercises
Test
Answers to Practice Exercises
Chapter 9 Polytomous Logistic Regression
Introduction
Abbreviated Outline
Objectives
Presentation
Detailed Outline
Practice Exercises
Test
Answers to Practice Exercises
Chapter 10 Ordinal Logistic Regression
Introduction
Abbreviated Outline
Objectives
Presentation
Detailed Outline
Practice Exercises
Test
Answers to Practice Exercises
Chapter 11 Logistic Regression for Correlated Data: GEE
Introduction
Abbreviated Outline
Objectives
Presentation
Detailed Outline
Practice Exercises
Test
Answers to Practice Exercises
Chapter 12 GEE Examples
Introduction
Abbreviated Outline
Objectives
Presentation
Detailed Outline
Practice Exercises
Test
Answers to Practice Exercises
Chapter 13 Other Approaches for Analysis of Correlated Data
Introduction
Abbreviated Outline
Objectives
Presentation
Detailed Outline
Practice Exercises
Test
Answers to Practice Exercises
Appendix: Computer Programs for Logistic Regression
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