Bayesian Biostatistics and Diagnostic Medicine

There are numerous advantages to using Bayesian methods in diagnostic medicine, which is why they are employed more and more today in clinical studies. Exploring Bayesian statistics at an introductory level, Bayesian Biostatistics and Diagnostic Medicine illustrates how to apply these methods to solve important problems in medicine and biology.After focusing on the wide range of areas where diagnostic medicine is used, the book introduces Bayesian statistics and the estimation of accuracy by sensitivity, specificity, and positive and negative predictive values for ordinal and continuous diagnostic measurements. The author then discusses patient covariate information and the statistical methods for estimating the agreement among observers. The book also explains the protocol review process for cancer clinical trials, how tumor responses are categorized, how to use WHO and RECIST criteria, and how Bayesian sequential methods are employed to monitor trials and estimate sample sizes.With many tables and figures, this book enables readers to conduct a Bayesian analysis for a large variety of interesting and practical biomedical problems.

Preface	p. ix
Acknowledgments	p. xi
Author	p. xiii
Introduction	p. 1
Introduction	p. 1
Statistical Methods in Diagnostic Medicine	p. 1
Preview of Book	p. 2
Datasets for the Book	p. 4
Software	p. 4
References	p. 5
Diagnostic Medicine	p. 7
Introduction	p. 7
Imaging Modalities	p. 7
Activities in Diagnostic Imaging	p. 11
Accuracy and Agreement	p. 12
Developmental Trials for Imaging	p. 14
Protocol Review and Clinical Trials	p. 15
The Protocol	p. 16
Phase I, II, and III Clinical Designs	p. 16
The Literature	p. 18
References	p. 18
Other Diagnostic Procedures	p. 21
Introduction	p. 21
Sentinel Lymph Node Biopsy for Melanoma	p. 21
Tumor Depth to Diagnose Metastatic Melanoma	p. 22
Biopsy for Nonsmall Cell Lung Cancer	p. 23
Coronary Artery Disease	p. 24
References	p. 24
Bayesian Statistics	p. 27
Introduction	p. 27
Bayes Theorem	p. 28
Prior Information	p. 29
Posterior Information	p. 33
Inference	p. 36
Introduction	p. 36
Estimation	p. 36
Testing Hypotheses	p. 38
Introduction	p. 38
Binomial Example of Testing	p. 39
Comparing Two Binomial Populations	p. 40
Sharp Null Hypothesis for the Normal Mean	p. 41
Sample Size	p. 41
Introduction	p. 41
A One-Sample Binomial for Response	p. 42
A One-Sample Binomial with Prior Information	p. 44
Comparing Two Binomial Populations	p. 45
Computing	p. 45
Introduction	p. 45
Direct Methods of Computation	p. 46
Gibbs Sampling	p. 49
Introduction	p. 49
Common Mean of Normal Populations	p. 50
MCMC Sampling with WinBUGS[Registered]	p. 53
Exercises	p. 56
References	p. 57
Bayesian Methods for Diagnostic Accuracy	p. 59
Introduction	p. 59
Study Design	p. 60
The Protocol	p. 60
Objectives	p. 60
Background	p. 61
Patient and Reader Selection	p. 61
Study Plan	p. 62
Number of Patients	p. 63
Statistical Design and Analysis	p. 63
References	p. 64
Bayesian Methods for Test Accuracy: Binary and Ordinal Data	p. 65
Introduction	p. 65
Classification Probabilities	p. 65
Predictive Values	p. 68
Diagnostic Likelihood Ratios	p. 69
ROC Curve	p. 69
Bayesian Methods for Test Accuracy: Quantitative Variables	p. 73
Introduction	p. 73
The Spokane Heart Study	p. 73
ROC Area	p. 74
Definition of the ROC Curve	p. 77
Choice of Optimal Threshold Value	p. 78
Clustered Data: Detection and Localization	p. 79
Introduction	p. 79
Bayesian ROC Curve for Clustered Information	p. 80
Clustered Data in Mammography	p. 82
Comparing Accuracy between Modalities	p. 84
Sample Size Determination	p. 87
Introduction	p. 87
Discrete Diagnostic Scores	p. 88
Binary Tests	p. 88
Multinomial Outcomes	p. 91
Sample Sizes: Continuous Diagnostic Scores	p. 92
One ROC Curve	p. 92
Two ROC Curves	p. 95
Exercises	p. 97
References	p. 99
Regression and Test Accuracy	p. 101
Introduction	p. 101
Audiology Study	p. 102
Introduction	p. 102
Log Link Function	p. 102
Logistic Link	p. 103
Diagnostic Likelihood Ratio	p. 105
ROC Area and Patient Covariates	p. 107
Introduction	p. 107
ROC Curve as Response to Therapy	p. 108
Diagnosing Prostate Cancer	p. 110
Exercises	p. 111
References	p. 111
Agreement	p. 113
Introduction	p. 113
Agreement for Discrete Ratings	p. 114
Binary Scores	p. 114
Other Indices of Agreement	p. 116
A Bayesian Version of McNemar	p. 117
Comparing Two Kappa Parameters	p. 117
Kappa and Stratification	p. 119
Multiple Categories and Two Readers	p. 120
Multiple Categories	p. 122
Agreement and Covariate Information	p. 123
Agreement for a Continuous Response	p. 126
Introduction	p. 126
Intra-Class Correlation Coefficient	p. 127
One-Way Random Model	p. 127
Two-Way Random Model	p. 131
Regression and Agreement	p. 132
Combining Reader Information	p. 134
Exercises	p. 136
References	p. 139
Diagnostic Imaging and Clinical Trials	p. 141
Introduction	p. 141
Clinical Trials	p. 142
Introduction	p. 142
Phase I Designs	p. 142
Phase II Trials	p. 143
Phase III Trials	p. 145
Protocol	p. 145
Guidelines for Tumor Response	p. 146
Bayesian Sequential Stopping Rules	p. 148
Software for Clinical Trials	p. 152
CRM Simulator for Phase I Trials	p. 153
Multc Lean for Phase II Trials	p. 153
Examples	p. 154
Phase I Trial for Renal Cell Carcinoma	p. 154
An Ideal Phase II Trial	p. 156
Phase II Trial for Advanced Melanoma	p. 158
Exercises	p. 162
References	p. 163
Other Topics	p. 165
Introduction	p. 165
Imperfect Diagnostic Test Procedures	p. 166
Extreme Verification Bias	p. 166
Verification Bias	p. 170
Estimating Test Accuracy with No Gold Standard	p. 173
Test Accuracy and Survival Analysis	p. 178
ROC Curves with a Non-Binary Gold Standard	p. 180
Periodic Screening in Cancer	p. 182
Inference for Sensitivity and Transition Probability	p. 182
Bayesian Inference for Lead-Time	p. 186
Decision Theory and Diagnostic Accuracy	p. 189
Exercises	p. 192
References	p. 193
Index	p. 195
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 Biostatistics and Diagnostic Medicine

Summary

Table of Contents

Supplemental Materials