Ordinal data modeling
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Author
Contributions
- Albert, Jim, 1953- - Contributor
Publication
1999 - Springer, New York, New York (State)
Language
English
Word Count
64,500 words, Guess
Page Count
258 pages
Identifiers
- Open LibraryOL388558M
- ISBN-100387987185
- OCLC Control Number98051801
- OCLC Control Number40354878
- OCLC Control Numberordinaldatamodel00john_320
and 3 more
- Library of Congress Control Number98051801
- Goodreads1694683
- LibraryThing4244039
Classifications
- DDC519.5
- LCCHA29 .J588 1999
Description
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.
Subjects
Topics
Series Statement
- Statistics for social science and public policy
Other Editions
- Ordinal data modeling
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