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Logistic Regression David G. Kleinbaum

Logistic Regression By David G. Kleinbaum

Logistic Regression by David G. Kleinbaum


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Summary

A text on logistic regression methods. It includes chapters that contain a presentation of its topic in 'lecture-book' format together with objectives, an outline, key formulae, practice exercises, and a test.

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Logistic Regression Summary

Logistic Regression: A Self-learning Text by David G. Kleinbaum

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 of this title are: Chapter 9 - Polytomous Logistic Regression; Chapter 10 - Ordinal Logistic Regression; Chapter 11 - Logistic Regression for Correlated Data; Chapter 12 - GEE Examples; and, 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.

Table of Contents

Introduction to Logistic Regression.- Important Special Cases of the Logistic Model.- Computing the Odds Ratio in Logistic Regression.- Maximum Likelihood Techniques: An Overview.- Statistical Inferences Using Maximum Likelihood Techniques.- Modeling Strategy Guidelines.- Modeling Strategy for Assessing Interaction and Confounding.- Analysis of Matched Data Using Logistic Regression.- Polytomous Logistic Regression.- Ordinal Logistic Regression.- Logistic Regression for Correlated Data: GEE.- GEE Examples.- Other Approaches for Analysis of Correlated Data.- Appendix: Computer Programs for Logistic Regression.- Test Answers.- Bibliography.- Index.

Additional information

CIN0823055531G
9780823055531
0823055531
Logistic Regression: A Self-learning Text by David G. Kleinbaum
Used - Good
Hardback
Springer-Verlag New York Inc.
20020812
527
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in good condition, but if you are not entirely satisfied please get in touch with us

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