Ordinal Data Modeling

  • Valen E. Johnson
  • James H. Albert

Table of contents

About this book

Introduction

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.

Keywords

Bayesian inference DEX Statistica computation data model data modelling framework likelihood modeling ordinal review software

Authors and affiliations

  • Valen E. Johnson
    • 1
  • James H. Albert
    • 2
  1. 1.Institute of Statistics and Decision SciencesDuke UniversityDurhamUSA
  2. 2.Department of Mathematics and StatisticsBowling Green State UniversityBowling GreenUSA

Bibliographic information

  • DOI https://doi.org/10.1007/b98832
  • Copyright Information Springer-Verlag New York, Inc. 1999
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-98718-7
  • Online ISBN 978-0-387-22702-3
  • About this book