Klein M., Rihl Pryor E., Kleinbaum D.G. Logistic Regression: a Selft Learning Text

New York: Springer, 2010. — 709 p.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 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. This very popular textbook is now in its third edition. Whether students or working professionals, readers apprciate its unique "lecture book" format. They often say the book reads like they are listening to an outstanding lecture. This edition includes three new chapters, an updated computer appendix, and an expanded section about modeling guidelines that consider causal diagrams.Introduction 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 guideline
Modeling strategy for assessing interaction and confounding
Additional modeling strategy issues
Assessing goodness of fit for logistic regression
Assessing discriminatory performance of a binary logistic model: ROC curves
Analysis of matched data using logistic regression
Polytomous logistic regression
Ordinal logistic regression
Logistic regression for correlated data: GEE
GEE examples
Other approaches for analysis of correlated data
Computer programs for logistic regression.