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.
Publisher: Springer-Verlag New York Inc.
Number of pages: 258
Weight: 1250 g
Dimensions: 234 x 156 x 17 mm
Edition: 1st ed. 1999. Corr. 2nd printing 2000
From the reviews:
STATISTICAL METHODS IN MEDICAL RESEARCH
"The book is an excellent introduction to Bayesian methods of original data modeling...the book is well written and all concepts are presented in a clear manner. Notation is consistent throughout the book and ideas in later chapters logically build on previous material. Fundamental concepts discussed by the authors are well presented. The authors are particularly savvy at connecting new ideas to previous knowledge. This book would make an excellent supplementary text to an individual doing research in these areas...This book does provide valuable information about modeling original data using Bayesian methods. This text provides a valuable addition to a researcher's library (especially those working in psychometrics or educational statistics)."
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