【免费分享】 Logistic Regression By David G. Kleinbaum (2010 2ed)

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Logistic Regression: A Self-learning Text By David G. Kleinbaum
Publisher: Springer 2010 | 616 Pages | ISBN: 1441917411 | PDF | 12 MB



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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关键词：regression regressio Kleinbaum logistic regress 分享 David regression logistic Kleinbaum

谢谢楼主。

dwl001 发表于 2010-6-18 04:26


Logistic Regression: A Self-learning Text By David G. Kleinbaum
Publisher: Springer 2010 | 616 Pages | ISBN: 1441917411 | PDF | 12 MB



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.

谢谢
是第三版
In this appendix, we provide examples of computer programs to carry out unconditional
logistic regression, conditional logistic regression, polytomous logistic regression,
ordinal logistic regression, and GEE logistic regression. This appendix does not
give an exhaustive survey of all computer packages currently available, but rather is
intended to describe the similarities and differences among a sample of the most
widely used packages. The software packages that
we consider are
SAS version 9.2,
SPSS version 16.0, and
Stata version 10.0.
A detailed description of these packages is
beyond the scope of this appendix. Readers are referred to the built-in Help functions
for each program for further information.

呵呵，放到别的版块，更合适点。

这是好书啊！刚出发就免费了！lz好人！

超级感谢楼主免费发新书！

感谢宅心仁厚的楼主！

确实是第3版本

Thanks very much!

非常感谢！

感谢 lz ！！