Ordinal Data Modeling

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Springer Science & Business Media, Apr 6, 2006 - Social Science - 258 pages
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.
 

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Contents

Review of Classical and Bayesian Inference
1
6
14
2
16
6
26
Review of Bayesian Computation
33
7
41
Regression Models for Binary Data
75
7
81
Analyzing Data from Multiple Raters
158
Item Response Modeling
182
13
194
A Case Study of Undergraduate Grade
215
Software for Ordinal Data Modeling
239
References
249
Index
255
Copyright

Regression Models for Ordinal Data
126

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