Interpreting Effects in Logistic Regression and Logit Models shows how to compare coefficient estimates from regression models for categorical dependent variables in three typical research situations: (i) within one model, (ii) between identical models estimated in different subgroups, and (iii) between nested models. Additionally, this volume presents a practical, unified treatment of comparison problems and considers the advantages and disadvantages of each approach and when to use them.
This book has very clear, pristine explanations of topics such as how DRMs work, great numerical methods for maximizing and specifying, and helpful explanatory tests and interpretative effects, all written at an intermediate level. The discussion of various ways of interpreting coefficients in each of the models is the most useful part of the text. While many other texts touch on the difficulties of interpreting coefficients and perhaps offer an approach or two, the authors of this volume thoroughly review multiple approaches common and unique to each of the models. -- Kara Sutton
This book has a well-organized structure and includes coverage of useful information and skills in the logistic regression. Scholars can apply these models to their own research projects. -- Jingshun Zhang
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