Bayesian Methods for Measures of Agreement

Bayesian Methods for Measures of Agreement

by Lyle D. Broemeling
     
 

ISBN-10: 1420083414

ISBN-13: 9781420083415

Pub. Date: 01/14/2009

Publisher: Taylor & Francis

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

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Overview

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

ISBN-13:
9781420083415
Publisher:
Taylor & Francis
Publication date:
01/14/2009
Series:
Chapman & Hall/CRC Biostatistics Series, #29
Pages:
340
Product dimensions:
6.10(w) x 9.40(h) x 1.00(d)

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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