Hosmer, David WSturdivant, Rodney X
John Wiley & Sons (Hoboken, NJ, 2013) (eng) English9780470582473Unknown3rd ed.REGRESSION ANALYSIS; Unknown "A new edition of the definitive guide to logistic regression modeling for health science and other applicationsThis 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"-- Provided by publisher.
"This Third Edition continues to focus on applications and interpretation of results from fitting regression models to categorical response variables"-- Provided by publisher.
Physical dimension
xvi, 500 p.25 cm.ill.
Summary / review / table of contents
1. Introduction to the logistic regression model –
2. The multiple logistic regression model –
3. Interpretation of the coefficients of the logistic regression model –
4. Model-building strategies and methods for logistic regression –
5. Assessing the fit of the model –
6. Application of logistic regression with different sampling models –
7. Logistic regression for matched case-control studies –
8. Special topics.