A new edition of the definitive guide to logistic regression modeling for health science and other applications
This comprehensively expanded, Applied Logistic Regression, 3rd Edition, (PDF) 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, stresses applications in the health sciences and handpicks topics that best suit the use of modern statistical software. This thoroughly expanded 3rd 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.
The ebook provides readers with state-of-the-art techniques for constructing, interpreting, and assessing the performance of LR models. New and updated features include:
- A chapter on the analysis of correlated outcome data
- 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
- A wealth of additional material for topics ranging from Bayesian methods to assessing model fit
Applied Logistic Regression, 3rd Edition is a must-have guide for researchers and professionals who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences in addition to a wide range of other fields and disciplines.
NOTE: The product includes the ebook, Applied Logistic Regression, 3e in PDF. No access codes are included.