Bayesian Methods for Measures of Agreement

Using WinBUGS to implement Bayesian inferences of estimation and testing hypotheses,Bayesian Methods for Measures of Agreementpresents 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 Gcoefficient, and intraclass correlation. With examples throughout and end-of-chapter exercises, it discusses how to successfully design and analyze an agreement study.

Preface	p. xi
Acknowledgments	p. xiii
Author	p. xv
Introduction to Agreement	p. 1
Introduction	p. 1
Agreement and Statistics	p. 3
The Bayesian Approach	p. 5
Some Examples of Agreement	p. 7
The Lennox Lewis-Evander Holyfield Bout	p. 7
Phase II Clinical Trials	p. 10
Agreement on Tumor Size	p. 10
Wine Tasting	p. 15
Forgery: Robinson versus Mandell	p. 21
Sources of Information	p. 22
Software and Computing	p. 23
A Preview of the Book	p. 24
Exercises	p. 30
References	p. 31
Bayesian Methods of Agreement for Two Raters	p. 35
Introduction	p. 35
The Design of Agreement Studies	p. 36
Precursors of Kappa	p. 38
Chance Corrected Measures of Agreement	p. 41
Conditional Kappa	p. 42
Kappa and Stratification	p. 45
Weighted Kappa	p. 49
Intraclass Kappa	p. 51
Other Measures of Agreement	p. 55
Agreement with a Gold Standard	p. 59
Kappa and Association	p. 62
Consensus	p. 65
Exercises	p. 66
References	p. 69
More than Two Raters	p. 71
Introduction	p. 71
Kappa with Many Raters	p. 72
Partial Agreement	p. 78
Stratified Kappa	p. 83
Intraclass Kappa	p. 91
The Fleiss Generalized Kappa	p. 94
The G Coefficient and Other Indices	p. 97
Kappa and Homogeneity	p. 99
Introduction to Model Based Approaches	p. 100
Agreement and Matching	p. 103
Exercises	p. 104
References	p. 109
Agreement and Correlated Observations	p. 111
Introduction	p. 111
An Example of Paired Observations	p. 112
The Oden Pooled Kappa and Schouten Weighted Kappa	p. 118
A Generalized Correlation Model	p. 119
The G Coefficient and Other Indices of Agreement	p. 124
Homogeneity with Dependent Data	p. 125
Logistic Regression and Agreement	p. 130
Exercises	p. 138
References	p. 142
Modeling Patterns of Agreement	p. 145
Introduction	p. 145
Nominal Responses	p. 147
Ordinal Responses	p. 167
More than Two Raters	p. 173
Other Methods for Patterns of Agreement	p. 177
Summary of Modeling and Agreement	p. 182
Exercises	p. 183
References	p. 191
Agreement with Quantitative Scores	p. 193
Introduction	p. 193
Regression and Correlation	p. 194
The Analysis of Variance	p. 199
Intraclass Correlation Coefficient for Agreement	p. 204
Agreement with Covariates	p. 209
Other Considerations with Continuous Scores	p. 212
Introduction	p. 212
Bayesian Bland-Altman	p. 213
More on Variance Components	p. 215
Fixed Effects for Agreement	p. 216
Multivariate Techniques	p. 220
Exercises	p. 222
References	p. 233
Sample Sizes for Agreement Studies	p. 235
Introduction	p. 235
The Classical and Bayesian Approaches to Power Analysis	p. 238
The Standard Populations: Classical and Bayesian Approaches	p. 239
Kappa, the G Coefficient, and Other Indices	p. 245
The Logistic Linear Model	p. 252
Regression and Correlation	p. 255
The Intraclass Correlation	p. 260
Bayesian Approaches to Sample Size	p. 266
Exercises	p. 267
References	p. 271
Bayesian Statistics	p. 273
Introduction	p. 273
Bayes Theorem	p. 274
Prior Information	p. 276
Posterior Information	p. 278
Inference	p. 280
Introduction	p. 280
Estimation	p. 280
Testing Hypotheses	p. 282
Introduction	p. 282
A Binomial Example	p. 283
Comparing Two Binomials	p. 284
A Sharp Null Hypothesis for the Normal Mean	p. 284
Comparing Two Normal Populations	p. 285
Predictive Inference	p. 286
Introduction	p. 286
The Binomial	p. 287
Forecasting from a Normal Population	p. 287
Checking Model Assumptions	p. 288
Introduction	p. 288
Sampling from an Exponential, but Assuming a Normal Population	p. 289
Speed of Light Study of Newcomb	p. 290
A Poisson Population	p. 292
Measuring Tumor Size	p. 292
Testing the Multinomial Assumption	p. 293
Sample Size Problems	p. 294
Introduction	p. 294
The One Sample Binomial	p. 295
One Sample Binomial with Prior Information	p. 296
Comparing Two Binomial Populations	p. 297
Computing	p. 298
Introduction	p. 298
Direct Methods	p. 299
Monte Carlo Markov Chain	p. 303
Introduction	p. 303
The Metropolis Algorithm	p. 303
Gibbs Sampling	p. 304
The Common Mean of Normal Populations	p. 305
MCMC Sampling with WinBUGS	p. 309
Exercises	p. 312
References	p. 313
Introduction to WinBUGS	p. 315
Introduction	p. 315
Download	p. 316
The Essentials	p. 316
Main Body	p. 316
List Statements	p. 316
Execution	p. 316
The Specification Tool	p. 318
The Sample Monitor Tool	p. 318
The Update Tool	p. 318
Output	p. 319
Examples	p. 320
Kappa	p. 321
Logistic Linear Model	p. 323
Summary	p. 325
References	p. 325
Index	p. 327
Table of Contents provided by Ingram. All Rights Reserved.

What is included with this book?

The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.

The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.

FREE SHIPPING

Amazon no longer offers textbook rentals. We do!

Bayesian Methods for Measures of Agreement

Summary

Table of Contents

Supplemental Materials