This text presents an overview of the full range of logistic models, including binary, proportional, ordered, and categorical response regression procedures. It illustrates how to apply the models to medical, health, environmental/ecological, physical, and social science data. Stata is used to develop, evaluate, and display most models while R code is given at the end of most chapters. The author examines the theoretical foundation of the models and describes how each type of model is established, interpreted, and evaluated as to its goodness of fit. Example data sets are available online in various formats and a solutions manual is available upon qualifying course adoption.

Preface. Introduction. Concepts Related to the Logistic Model. Estimation Methods. Derivation of the Binary Logistic Algorithm. Model Development. Interactions. Analysis of Model Fit. Binomial Logistic Regression. Overdispersion. Ordered Logistic Regression. Multinomial Logistic Regression. Alternative Categorical Response Models. Panel Models. Other Types of Logistic-Based Models. Exact Logistic Regression. Conclusion. Appendices. References. Indices.