The focus in Applied Logistic Regression Analysis, Second Edition, is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. The book includes detailed discussions of goodness of fit, indices of predictive efficiency, and standardized logistic regression coefficients, and examples using SAS and SPSS are included. It has detailed consideration of grouped as opposed to case-wise data throughout the book and an updated discussion of the properties and appropriate use of goodness of fit measures, R-square analogues, and indices of predictive efficiency. The book includes a discussion of the misuse of odds ratios to represent risk ratios, and of over-dispersion and under-dispersion for grouped data. In addition to that it has updated coverage of unordered and ordered polytomous logistic regression models.