Logistic Regression - A Self-Learning Text (Hardcover, 3rd ed. 2010)

This is the third edition of this text on logistic regression methods, originally published in 1994, with its second e- tion published in 2002. As in the first two editions, each chapter contains a pres- tation 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, formulae, or summary statements 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 third edition has expanded the second edition by adding three new chapters and a modified computer appendix. We have also expanded our overview of mod- ing strategy guidelines in Chap. 6 to consider causal d- grams. The three new chapters are as follows: Chapter 8: Additional Modeling Strategy Issues Chapter 9: Assessing Goodness of Fit for Logistic Regression Chapter 10: Assessing Discriminatory Performance of a Binary Logistic Model: ROC Curves In adding these three chapters, we have moved Chaps. 8 through 13 from the second edition to follow the new chapters, so that these previous chapters have been ren- bered as Chaps. 11-16 in this third edition.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Statistics for Biology and Health
Release date:	July 2010
First published:	July 2010
Authors:	David G. Kleinbaum • Mitchel Klein
Dimensions:	254 x 178 x 47mm (L x W x T)
Format:	Hardcover
Pages:	702
Edition:	3rd ed. 2010
ISBN-13:	978-1-4419-1741-6
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Social sciences > Sociology, social studies > Social research & statistics > General Books > Medicine > General issues > Public health & preventive medicine > Epidemiology & medical statistics Promotions > Red Tag Sale > Books
LSN:	1-4419-1741-1
Barcode:	9781441917416

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