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.