The problem of grade inflation has received much attention in the media. Johnson's book is unique in that he has data to show that grade inflation is primarily the result of grading practices by humanities instructors, and that one of the major causes is the way in which student evaluations are used.

Ordinal Data Modeling is a comprehensive treatment of ordinal data models from both likelihood and Bayesian perspectives. Written for graduate students and researchers in the statistical and social sciences, this book describes a coherent framework for understanding binary and ordinal regression models, item response models, graded response models, and ROC analyses, and for exposing the close connection between these models. A unique feature of this text is its emphasis on applications. All models developed in the book are motivated by real datasets, and considerable attention is devoted to the description of diagnostic plots and residual analyses. Software and datasets used for all analyses described in the text are available on websites listed in the preface.

Ordinal Data Modeling is a comprehensive treatment of ordinal data models from both likelihood and Bayesian perspectives. A unique feature of this text is its emphasis on applications. All models developed in the book are motivated by real datasets, and considerable attention is devoted to the description of diagnostic plots and residual analyses. Software and datasets used for all analyses described in the text are available on websites listed in the preface.

Grade inflation runs rampant at most colleges and universities, but faculty and administrators are seemingly unwilling to face the problem. This book explains why, exposing many of the misconceptions surrounding college grading. Based on historical research and the results of a yearlong, on-line course evaluation experiment conducted at Duke University during the 1998-1999 academic year, the effects of student grading on various educational processes, and their subsequent impact on student and faculty behavior, is examined. Principal conclusions of this investigation are that instructors' grading practices have a significant influence on end-of-course teaching evaluations, and that student expectations of grading practices play an important role in the courses that students decide to take. The latter effect has a serious impact on course enrollments in the natural sciences and mathematics, while the combination of both mean that faculty have an incentive to award high grades, and students have an incentive to choose courses with faculty who do. Grade inflation is the natural consequence of this incentive system. Material contained in this book is essential reading for anyone involved in efforts to reform our postsecondary educational system, or for those who simply wish to survive and prosper in it.

Valen Johnson is a Professor of Biostatistics at the University of Michigan. Prior to accepting an appointment in Ann Arbor, he was a Professor of Statistics and Decision Sciences at Duke University, where data for this book was collected. He is a Fellow of the American Statistical Association.