Publisher description for Logistic regression : a self-learning text / David G. Kleinbaum, Mitchel Klein ; with contributions by Erica Rihl Pryor.

Bibliographic record and links to related information available from the Library of Congress catalog

Information from electronic data provided by the publisher. May be incomplete or contain other coding.

This very popular textbook is now in its third edition. Whether students or working professionals, readers appreciate its unique "lecture book" format. They often say the book reads like they are listening to an outstanding lecturer. This edition includes three new chapters, an updated computer appendix, and an expanded section about modeling guidelines that consider causal diagrams. Like previous editions, this textbook provides a highly readable description of fundamental and more advanced concepts and methods of logistic regression. It is suitable for researchers and statisticians in medical and other life sciences as well as academicians teaching second-level regression methods courses. The new chapters are: Additional Modeling Strategy Issues, including strategy with several exposures, screening variables, collinearity, influential observations and multiple-testing, assessing Goodness to Fit for Logistic Regression, assessing Discriminatory Performance of a Binary Logistic Model: ROC Curves. The Computer Appendix provides step-by-step instructions for using STATA (version 10.0), SAS (version 9.2), and SPSS (version 16) for procedures described in the main text.

Library of Congress subject headings for this publication:
Medicine -- Research -- Statistical methods.
Regression analysis.
Logistic distribution.