Ordinal Data Modeling
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.
1117015988
Ordinal Data Modeling
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.
54.99 In Stock
Ordinal Data Modeling

Ordinal Data Modeling

Ordinal Data Modeling

Ordinal Data Modeling

Hardcover(1999)

$54.99 
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Overview

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.

Product Details

ISBN-13: 9780387987187
Publisher: Springer New York
Publication date: 03/30/1999
Series: Statistics for Social and Behavioral Sciences
Edition description: 1999
Pages: 258
Product dimensions: 6.10(w) x 9.25(h) x (d)

Table of Contents

Review of Classical and Bayesian Inference.- Review of Bayesian Computation.- Regression Models for Binary Data.- Regression Models for Ordinal Data.- Analyzing Data from Multiple Raters.- Item Response Modeling.- Graded Response Models: A Case Study of Undergraduate Grade Data.
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