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## Details

Genre/Form: | Electronic books |
---|---|

Additional Physical Format: | Print version: |

Material Type: | Document, Internet resource |

Document Type: | Internet Resource, Computer File |

All Authors / Contributors: |
Lyle D Broemeling |

ISBN: | 9781439838792 1439838798 1322614385 9781322614380 |

OCLC Number: | 775570655 |

Notes: | "A Chapman & Hall book." |

Description: | 1 online resource (xix, 450 pages) : illustrations. |

Contents: | 1. Introduction -- 2. Medical tests and preliminary information -- 3. Preview of the book -- 4. Fundamentals of diagnostic accuracy -- 5. Regression and medical test accuracy -- 6. Agreement and test accuracy -- 7. Estimating test accuracy with an imperfect reference standard -- 8. Verification bias and test accuracy -- 9. Test accuracy and medical practice -- 10. Accuracy of combined tests -- 11. Bayesian methods of meta-analysis. |

Series Title: | Chapman & Hall/CRC biostatistics series. |

Responsibility: | Lyle D. Broemeling. |

More information: |

### Abstract:

## Reviews

*Editorial reviews*

Publisher Synopsis

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 referencesIntegrates reader agreement with different modalities-X-ray, CT Scanners, and more-to study their effect on medical test accuracyProvides practical chapter-end problemsUseful 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. IntroductionIntroduction Statistical Methods in Medical Test AccuracyDatasets for This Book Software Bayesian Approach ReferencesMedical Tests and Preliminary InformationIntroduction Medical Imaging Tests Other Medical Tests Activities Involved in Medical Testing Accuracy and AgreementDevelopmental Trials for Medical Devices Literature ReferencesPreview of the BookIntroduction Preliminary InformationFundamentals of Test AccuracyAdvanced Methods for Test Accuracy ReferencesFundamentals of Diagnostic AccuracyIntroduction Study Design Bayesian Methods for Test Accuracy: Binary and Ordinal Data Clustered Data: Detection and LocalizationComparing Accuracy between Modalities with Ordinal ScoresExercises ReferencesRegression and Medical Test AccuracyIntroduction Audiology Study Receiver Operating Characteristic Area and Patient CovariatesRegression Methods for Continuous Test Scores Exercises ReferencesAgreement and Test AccuracyIntroduction 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 ConsensusAgreement with Multiple Raters and Ordinal Scores-No Gold StandardConclusions for Agreement and Accuracy Exercises ReferencesEstimating Test Accuracy with an Imperfect Reference Standard Introduction Two Binary TestsPosterior Distribution for Two Binary Tests Posterior Distribution without Conditional IndependencePosterior Distribution Assuming Conditional IndependenceExample of Accuracy for Diagnosing a Bacterial InfectionAccuracies of Two Binary Tests for Several Populations with Conditional IndependenceAccuracies of Two Binary Tests without Conditional Independence: Two PopulationsMultiple Tests in a Single Population Multiple Tests without Conditional IndependenceTwo Ordinal Tests and the Receiver OperatingCharacteristic Area Exercises ReferencesVerification Bias and Test AccuracyIntroduction Verification Bias and Binary Tests Two Binary TestsOrdinal Tests and Verification BiasTwo 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 AreaComments and Conclusions Exercises ReferencesTest Accuracy and Medical PracticeIntroduction Choice of Optimal ThresholdTest Accuracy with Bayesian Decision CurvesTest Accuracy and Clinical Trials Summary and Conclusions Exercises ReferencesAccuracy of Combined TestsIntroduction Two Binary TestsTwo Binary Tests and Several ReadersAccuracy of Combined Binary Tests with Verification BiasLikelihood Ratio, the Risk Score, the Neyman-Pearson Lemma, and the Accuracy of Multiple Ordinal TestsAccuracy of the Combined Test for Continuous ScoresObservations and Conclusions Exercises ReferencesBayesian Methods for Meta-AnalysisIntroduction 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-AnalysesComments and Conclusions Exercises ReferencesAppendix: Introduction to WinBUGSIntroduction Download Essentials OutputAnother ExampleSummary References "â ¦ 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. â ¦ 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. â ¦ The literature review supporting the theoretical concepts about accuracy and the practical aspects associated with the applications is without a doubt extensive. â ¦ a good overview of the methods currently used to assess the accuracy of a medical test and their transposition to the Bayesian framework."-Benoit 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. â ¦ 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 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. Introduction Introduction Statistical Methods in Medical Test Accuracy Datasets for This Book Software Bayesian Approach References Medical Tests and Preliminary Information Introduction Medical Imaging Tests Other Medical Tests Activities Involved in Medical Testing Accuracy and Agreement Developmental Trials for Medical Devices Literature References Preview of the Book Introduction Preliminary Information Fundamentals of Test Accuracy Advanced Methods for Test Accuracy References Fundamentals of Diagnostic Accuracy Introduction Study Design Bayesian Methods for Test Accuracy: Binary and Ordinal Data Clustered Data: Detection and Localization Comparing Accuracy between Modalities with Ordinal Scores Exercises References Regression and Medical Test Accuracy Introduction Audiology Study Receiver Operating Characteristic Area and Patient Covariates Regression Methods for Continuous Test Scores Exercises References Agreement and Test Accuracy Introduction 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 Consensus Agreement with Multiple Raters and Ordinal Scores-No Gold Standard Conclusions for Agreement and Accuracy Exercises References Estimating Test Accuracy with an Imperfect Reference Standard Introduction 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 Exercises References Verification Bias and Test Accuracy Introduction 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 Exercises References Test Accuracy and Medical Practice Introduction Choice of Optimal Threshold Test Accuracy with Bayesian Decision Curves Test Accuracy and Clinical Trials Summary and Conclusions Exercises References Accuracy of Combined Tests Introduction 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 Exercises References Bayesian Methods for Meta-Analysis Introduction 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 Exercises References Appendix: Introduction to WinBUGS Introduction Download Essentials Output Another Example Summary References 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. 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. Read more...

*User-contributed reviews*

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### Related Subjects:(11)

- Diagnosis -- Statistical methods.
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