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. The book 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.
关于作者
DAVID W. HOSMER, Jr., Ph D, is Professor Emeritus of
Biostatistics at the School of Public Health and Health Sciences at
the University of Massachusetts Amherst.
STANLEY LEMESHOW, Ph D, is Professor of Biostatistics and
Founding Dean of the College of Public Health at The Ohio State
University, Columbus, Ohio.
RODNEY X. STURDIVANT, Ph D, 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.
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