Logistic Regression A Self-Learning Text /

• Main Authors: Kleinbaum, David G. (Author), Klein, Mitchel. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic
• Language: English
• Published: New York, NY : Springer New York, 2002.
• Edition: Second Edition.
• Series: Statistics for Biology and Health,
• Subjects: Statistics.; Epidemiology.; Statistics for Life Sciences, Medicine, Health Sciences.; Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law.
• Online Access: View fulltext via EzAccess

This is the second edition of this text on logistic regression methods, ori- nally published in 1994. As in the first edition, each chapter contains a presentation of its topic in ỚSlecture-bookỚ<U+00fd> format together with objectives, an outline, key formulae, practice exercises, and a tes...

Table of Contents:

• 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 Guidelines
• Modeling Strategy for Assessing Interaction and Confounding
• Analysis of Matched Data Using Logistic Regression
• Polytomous Logistic Regression
• Ordinal Logistic Regression
• Logistic Regresion for Correlated Data: GEE
• GEE Examples
• Other Approaches for Analysis of Correlated Data.