A new edition of the definitive guide to logistic regression modeling for health science and other applications
This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables.
Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. Applied Logistic Regression provides readers with state-of-the-art techniques for building, interpreting, and assessing the performance of LR models. New and updated features include:
- A chapter on the analysis of correlated outcome data
- A wealth of additional material for topics ranging from Bayesian methods to assessing model fit
- Rich data sets from real-world studies that demonstrate each method under discussion
- Detailed examples and interpretation of the presented results as well as exercises throughout
Applied Logistic Regression, Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences as well as a wide range of other fields and disciplines.
Preface to the Third Edition xiii
1 Introduction to the Logistic Regression Model 1
2 The Multiple Logistic Regression Model 35
3 Interpretation of the Fitted Logistic Regression Model 49
4 Model-Building Strategies and Methods for Logistic Regression 89
5 Assessing the Fit of the Model 153
6 Application of Logistic Regression with Different Sampling Models 227
7 Logistic Regression for Matched Case-Control Studies 243
8 Logistic Regression Models for Multinomial and Ordinal Outcomes 269
9 Logistic Regression Models for the Analysis of Correlated Data 313
10 Special Topics 377
Index 479
David W Hosmer is Professor Emeritus of Biostatistics at the School of Public Health and Health Sciences at the University of Massachusetts Amherst. Stanley Lemeshow, PhD, is Professor of Biostatistics and Founding Dean of the College of Public Health at The Ohio State University, Columbus, Ohio. Rodney X Sturdivant, PhD, is Associate Professor and Founding Director of the Center for Data Analysis and Statistics at the United States Military Academy at West Point, New York.
"In conclusion, the index was mercifully complete, and all items searched for were found (nice cross-referencing too) In summary: Highly recommended."
– Scientific Computing, 1 May 2013