Bayesian Methods for Measures of Agreement

Bayesian Methods for Measures of Agreement

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Description

Using WinBUGS to implement Bayesian inferences of estimation and testing hypotheses, Bayesian Methods for Measures of Agreement presents useful methods for the design and analysis of agreement studies. It focuses on agreement among the various players in the diagnostic process.





The author employs a Bayesian approach to provide statistical inferences based on various models of intra- and interrater agreement. He presents many examples that illustrate the Bayesian mode of reasoning and explains elements of a Bayesian application, including prior information, experimental information, the likelihood function, posterior distribution, and predictive distribution. The appendices provide the necessary theoretical foundation to understand Bayesian methods as well as introduce the fundamentals of programming and executing the WinBUGS software.





Taking a Bayesian approach to inference, this hands-on book explores numerous measures of agreement, including the Kappa coefficient, the G coefficient, and intraclass correlation. With examples throughout and end-of-chapter exercises, it discusses how to successfully design and analyze an agreement study.
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Product details

  • Hardback | 340 pages
  • 154 x 234 x 24mm | 621.42g
  • Chapman & Hall/CRC
  • Boca Raton, FL, United States
  • English
  • 28 Illustrations, black and white
  • 1420083414
  • 9781420083415
  • 1,644,161

Table of contents

Introduction to Agreement


Introduction


Agreement and Statistics


The Bayesian Approach


Some Examples of Agreement


Sources of Information


Software and Computing


A Preview of the Book


Bayesian Methods of Agreement for Two Raters


Introduction


The Design of Agreement Studies


Precursors of Kappa


Chance Corrected Measures of Agreement


Conditional Kappa


Kappa and Stratification


Weighted Kappa


Intraclass Kappa


Other Measures of Agreement


Agreement with a Gold Standard


Kappa and Association


Consensus


More Than Two Raters


Introduction


Kappa with Many Raters


Partial Agreement


Stratified Kappa


Intraclass Kappa


The Fleiss Generalized Kappa


The G Coefficient and Other Indices


Kappa and Homogeneity


Introduction to Model-Based Approaches


Agreement and Matching


Agreement and Correlated Observations


Introduction


An Example of Paired Observations


The Oden Pooled Kappa and Schouten Weighted Kappa


A Generalized Correlation Model


The G Coefficient and Other Indices of Agreement


Homogeneity with Dependent Data


Logistic Regression and Agreement


Modeling Patterns of Agreement


Introduction


Nominal Responses


Ordinal Responses


More than Two Raters


Other Methods for Patterns of Agreement


Summary of Modeling and Agreement


Agreement with Quantitative Scores


Introduction


Regression and Correlation


The Analysis of Variance


Intraclass Correlation Coefficient for Agreement


With Covariates


Other Considerations with Continuous Scores


Sample Sizes for Agreement Studies


Introduction


The Classical and Bayesian Approaches to Power Analysis


The Standard Populations: Classical and Bayesian Approaches


Kappa, the G Coefficient, and Other Indices


The Logistic Linear Model


Regression and Correlation


The Intraclass Correlation


Bayesian Approaches to Sample Size


Appendix A: Bayesian Statistics


Introduction


Bayes Theorem


Prior Information


Posterior Information


Inference


Predictive Inference


Checking Model Assumptions


Sample Size Problems


Computing


Appendix B: Introduction to WinBUGS


Introduction


Download


The Essentials


Execution


Output


Examples


Summary


Exercises appear at the end of each chapter.
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Review quote

"This book is a welcome addition to the literature on Bayesian inference as it presents methods for the design and analysis of agreement studies. ... The approach presented by the author is novel and the novice will find a helpful introduction to Bayesian inference in an appendix. ... The text is readable and will form a valuable reference source. For those unfamiliar with WinBUGS, the author introduces the fundamentals of programming and executing BUGS."
-International Statistical Review, 2010


"This book deals with measures of agreement from a Bayesian perspective, focusing mainly on variants of Cohen's κ, but also other measures included in Shoukri (2003) and von Eye and Mun (2005), frequentist texts for which this book is intended to be a Bayesian companion. Dr. Broemeling uses examples throughout the book to illustrate concepts rather than resorting to jargon ... This book would be valuable for those using the methods in Shoukri and von Eye and Mun. ..."
-Journal of the Royal Statistical Society, Series A, Volume 173, Issue 1, January 2010
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About Lyle D. Broemeling

Medical Lake, Washington, USA
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