
Logistic Regression
A Self-Learning Text
Springer (Publisher)
2nd Edition
Published on 12. August 2002
Book
Hardback
XIV, 514 pages
978-0-387-95397-7 (ISBN)
Article exhausted; check for reprint
Description
This is the second edition of this text on logistic regression methods, ori- nally published in 1994. 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 illust- tions 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 has expanded the first edition by adding five new ch- ters and a new appendix. The five new chapters are Chapter 9. Polytomous Logistic Regression Chapter 10. Ordinal Logistic Regression Chapter 11. Logistic Regression for Correlated Data: GEE 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 gen- alized estimating equations (GEE) and other methods for analyzing cor- lated response data. The appendix is titled "Computer Programs for Logistic Regression" and p- vides descriptions and examples of computer programs for carrying out the variety of logistic regression procedures described in the main text. The so- ware packages considered are SAS Version 8.0, SPSS Version 10.0, and STATA Version 7.0.
More details
Series
Edition
2nd ed. 2002. Corr. 4th printing
Language
English
Place of publication
NY
United States
Target group
College/higher education
Professional and scholarly
Research
Edition type
Revised edition
Illustrations
105
105 s/w Abbildungen
105 black & white illustrations
Dimensions
Height: 27 cm
Width: 21 cm
Weight
1311 gr
ISBN-13
978-0-387-95397-7 (9780387953977)
DOI
10.1007/b97379
Schweitzer Classification
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05/1994
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Content
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 Regresion for Correlated Data: GEE.- GEE Examples.- Other Approaches for Analysis of Correlated Data.