Applied Logistic Regression Analysis

The focus in this Second Edition is on logistic regression models for individual level (but aggregate or grouped) data. Multiple cases for each possible combination of values of the predictors are considered in detail and examples using SAS and SPSS included. New to this edition: More detailed consideration of grouped as opposed to casewise data throughout the book Updated discussion of the properties and appropriate use of goodness of fit measures, R2 analogues, and indices of predictive efficiency Discussion of the misuse of odds ratios to represent risk ratios, and of overdispersion and underdispersion for grouped data Updated coverage of unordered and ordered polytomous logistic regression models.