Logistic Regression

Author:   David G Kleinbaum ,  Mitchel Klein
Publisher:   Springer
ISBN:  

9781441917607


Pages:   722
Publication Date:   28 February 2011
Format:   Undefined
Availability:   Out of stock   Availability explained


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Logistic Regression


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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.

Full Product Details

Author:   David G Kleinbaum ,  Mitchel Klein
Publisher:   Springer
Imprint:   Springer
Dimensions:   Width: 25.40cm , Height: 3.70cm , Length: 17.80cm
Weight:   1.229kg
ISBN:  

9781441917607


ISBN 10:   1441917608
Pages:   722
Publication Date:   28 February 2011
Audience:   General/trade ,  General
Format:   Undefined
Publisher's Status:   Unknown
Availability:   Out of stock   Availability explained

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