Logistic Regression: A Self-Learning Text / Edition 2

Logistic Regression: A Self-Learning Text / Edition 2

by David G. Kleinbaum, David G. Kleinbaum, Mitchell Klein
     
 

This is the second edition of this text on logistic regression methods. As in the first edition, each chapter contains a presentation of its topic in "lecture-book" format together with objectives, an outline, key formulae, practice exercises, and a test. The "lecture-book" has a sequence of illustrations and formulae in the left column of each page and a script (i.e.… See more details below

Overview

This is the second edition of this text on logistic regression methods. As in the first edition, each chapter contains a presentation of its topic in "lecture-book" format together with objectives, an outline, key formulae, practice exercises, and a test. The "lecture-book" has a sequence of illustrations and formulae in the left column of each page and a script (i.e., text) in the right column. This format allows you to read the script in conjunction with the illustrations and formulae that highlight the main points, formulae, or examples being presented.

This second edition includes five new chapters and an appendix. The new chapters are:

Chapter 9. Polytomous Logistic Regression

Chapter 10. Ordinal Logistic Regression

Chapter 11. Logistic Regression for Correlated Data

Chapter 12. GEE Examples

Chapter 13. Other Approaches for Analysis of Correlated Data

Chapters 9 and 10 extend logistic regression to response variables that have more than two categories. Chapters 11-13 extend logistic regression to generalized estimating equations (GEE) and other methods for analyzing correlated response data.

The appendix "Computer Programs for Logistic Regression" provides descriptions and examples of computer programs for carrying out the variety of logistic regression procedures described in the main text. The software packages considered are SAS Version 8.0, SPSS Version 10.0 and STATA Version 7.0.

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Product Details

ISBN-13:
9780387953977
Publisher:
Springer-Verlag New York, LLC
Publication date:
08/28/2002
Series:
Statistics for Biology and Health Series
Edition description:
REV
Pages:
513
Product dimensions:
8.10(w) x 9.30(h) x 1.30(d)

Related Subjects

Table of Contents

Preface
Acknowledgments
Ch. 1Introduction to Logistic Regression1
Ch. 2Important Special Cases of the Logistic Model39
Ch. 3Computing the Odds Ratio in Logistic Regression73
Ch. 4Maximum Likelihood Techniques: An Overview101
Ch. 5Statistical Inferences Using Maximum Likelihood Techniques125
Ch. 6Modeling Strategy Guidelines161
Ch. 7Modeling Strategy for Assessing Interaction and Confounding191
Ch. 8Analysis of Matched Data Using Logistic Regression227
Ch. 9Polytomous Logistic Regression267
Ch. 10Ordinal Logistic Regression301
Ch. 11Logistic Regression for Correlated Data: GEE327
Ch. 12GEE Examples377
Ch. 13Other Approaches for Analysis of Correlated Data405
AppComputer Programs for Logistic Regression437
Test Answers487
Bibliography503
Index507

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