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Advanced Bayesian Methods for Medical Test Accuracy


Useful in many areas of medicine and biology, Bayesian methods are particularly attractive tools for the design of clinical trials and diagnostic tests, which are based on established information, usually from related previous studies. Advanced Bayesian Methods for Medical Test Accuracy begins with a review of the usual measures such as specificity, sensitivity, positive and negative predictive value, and the area under the ROC curve. Then the scope expands to cover the more advanced topics of verification bias, ...

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Useful in many areas of medicine and biology, Bayesian methods are particularly attractive tools for the design of clinical trials and diagnostic tests, which are based on established information, usually from related previous studies. Advanced Bayesian Methods for Medical Test Accuracy begins with a review of the usual measures such as specificity, sensitivity, positive and negative predictive value, and the area under the ROC curve. Then the scope expands to cover the more advanced topics of verification bias, diagnostic tests with imperfect gold standards, and those for which no gold standard is available.

Promoting accuracy and efficiency of clinical trials, tests, and the diagnostic process, this book:

  • Enables the user to efficiently apply prior information via a WinBUGS package
  • Presents many ideas for the first time and goes far beyond the two standard references
  • Integrates reader agreement with different modalities—X-ray, CT Scanners, and more—to study their effect on medical test accuracy
  • Provides practical chapter-end problems

Useful for graduate students and consulting statisticians working in the various areas of diagnostic medicine and study design, this practical resource introduces the fundamentals of programming and executing BUGS, giving readers the tools and experience to successfully analyze studies for medical test accuracy.

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Editorial Reviews

From the Publisher
"… very thorough coverage of topics that are commonly encountered in practice as well as numerous examples. This book is particularly appropriate for graduate students in statistics who have interests in diagnostic medicine. It is also valuable to consulting statisticians who have some basic knowledge of Bayesian methods and need such a reference to solve practical problems. … a great introduction to Bayesian methods specifically focused on solving medical test accuracy-related problems. It addresses popular topics in medical accuracy studies via Bayesian statistical methods to take advantage of prior information. Some complex problems, such as situations without a gold standard and partial verification bias, are also discussed. I recommend this book to graduate students in statistics or biostatistics and applied statisticians who are interested in medical diagnostic test accuracy."
—Xiaoye Ma, Journal of the American Statistical Association, December 2013

"Dr. Broemeling places all these considerations associated with test accuracy determinations into a pure Bayesian perspective. His book can be, in some sense, considered as a Bayesian counterpart to the books of Pepe and Zhou et al. The presentation is quite detailed and supported by a significant number of applications. … The literature review supporting the theoretical concepts about accuracy and the practical aspects associated with the applications is without a doubt extensive. … a good overview of the methods currently used to assess the accuracy of a medical test and their transposition to the Bayesian framework."
—Benoît Beck, CHANCE, August 2013

"It covers extensively most aspects of applied problems one can encounter when dealing with diagnostic accuracy studies. An attractive feature is that WinBUGS code needed for the implementation of the described methodologies is given in every chapter (also available on the author’s blog). A set of exercises is given at the end of each chapter. … a carefully written book. It will be useful for consulting biostatisticians, graduate students and teachers using methods for the assessment of diagnostic accuracy from a Bayesian viewpoint. The book is a must have for the interested audience."
—Christos Nakas, ISCB Newsletter, June 2013

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Product Details

Meet the Author

Lyle D. Broemeling, Ph.D., is Director of Broemeling and Associates Inc., and is a consulting biostatistician. He has been involved with academic health science centers for about 20 years and has taught and been a consultant at the University of Texas Medical Branch in Galveston, The University of Texas MD Anderson Cancer Center and the University of Texas School of Public Health. His main interest is in developing Bayesian methods for use in medical and biological problems and in authoring textbooks in statistics. His previous books are Bayesian Analysis of Linear Models, Econometrics and Structural Change(written with Hiraki Tsurumi), Bayesian Biostatistics and Diagnostic Medicine, and Bayesian Methods for Agreement.

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Table of Contents

Statistical Methods in Medical Test Accuracy
Datasets for This Book
Bayesian Approach

Medical Tests and Preliminary Information
Medical Imaging Tests
Other Medical Tests
Activities Involved in Medical Testing
Accuracy and Agreement
Developmental Trials for Medical Devices

Preview of the Book
Preliminary Information
Fundamentals of Test Accuracy
Advanced Methods for Test Accuracy

Fundamentals of Diagnostic Accuracy
Study Design
Bayesian Methods for Test Accuracy: Binary and Ordinal Data
Clustered Data: Detection and Localization
Comparing Accuracy between Modalities with Ordinal Scores

Regression and Medical Test Accuracy
Audiology Study
Receiver Operating Characteristic Area and Patient Covariates
Regression Methods for Continuous Test Scores

Agreement and Test Accuracy
Ordinal Scores with a Gold Standard
Continuous Scores with a Gold Standard
Agreement with Ordinal Scores and No Gold Standard
Other Measures of Agreement
Agreement and Test Accuracy
Kappa and Association
Agreement with Multiple Raters and Ordinal Scores—No Gold Standard
Conclusions for Agreement and Accuracy

Estimating Test Accuracy with an Imperfect Reference Standard
Two Binary Tests
Posterior Distribution for Two Binary Tests
Posterior Distribution without Conditional Independence
Posterior Distribution Assuming Conditional Independence
Example of Accuracy for Diagnosing a Bacterial Infection
Accuracies of Two Binary Tests for Several Populations with Conditional Independence
Accuracies of Two Binary Tests without Conditional Independence: Two Populations
Multiple Tests in a Single Population
Multiple Tests without Conditional Independence
Two Ordinal Tests and the Receiver Operating
Characteristic Area

Verification Bias and Test Accuracy
Verification Bias and Binary Tests
Two Binary Tests
Ordinal Tests and Verification Bias
Two Ordinal Tests and Verification Bias
Two Ordinal Tests and Covariates
Inverse Probability Weighting
Without the Missing at Random Assumption
One Ordinal Test and the Receiver Operating Characteristic Area
Comments and Conclusions

Test Accuracy and Medical Practice
Choice of Optimal Threshold
Test Accuracy with Bayesian Decision Curves
Test Accuracy and Clinical Trials
Summary and Conclusions

Accuracy of Combined Tests
Two Binary Tests
Two Binary Tests and Several Readers
Accuracy of Combined Binary Tests with Verification Bias
Likelihood Ratio, the Risk Score, the Neyman–Pearson Lemma, and the Accuracy of Multiple Ordinal Tests
Accuracy of the Combined Test for Continuous Scores
Observations and Conclusions

Bayesian Methods for Meta-Analysis
Summary Receiver Operating Characteristic Curve and Bilogistic Regression
Bayesian Analysis for Summary Accuracy
Meta-Analysis with Two Tests
Meta-Analysis with Study Covariates and One Test
Meta-Analysis with Covariates for Several Tests
Other Meta-Analyses
Comments and Conclusions

Appendix: Introduction to WinBUGS
Another Example

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