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Statistical Evaluation of Diagnostic Performance

Topics in ROC Analysis

By Kelly H. Zou, Aiyi Liu, Andriy I. Bandos, Lucila Ohno-Machado, Howard E. Rockette

Chapman and Hall/CRC – 2011 – 245 pages

Series: Chapman & Hall/CRC Biostatistics Series

Purchasing Options:

  • Add to CartHardback: $98.95
    978-1-43-981222-8
    July 27th 2011

Description

Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (ROC) analysis in particular are important for assessing the performance of medical tests and statistical classifiers, as well as for evaluating predictive models or algorithms. This book presents innovative approaches in ROC analysis, which are relevant to a wide variety of applications, including medical imaging, cancer research, epidemiology, and bioinformatics.

Statistical Evaluation of Diagnostic Performance: Topics in ROC Analysis covers areas including monotone-transformation techniques in parametric ROC analysis, ROC methods for combined and pooled biomarkers, Bayesian hierarchical transformation models, sequential designs and inferences in the ROC setting, predictive modeling, multireader ROC analysis, and free-response ROC (FROC) methodology.

The book is suitable for graduate-level students and researchers in statistics, biostatistics, epidemiology, public health, biomedical engineering, radiology, medical imaging, biomedical informatics, and other closely related fields. Additionally, clinical researchers and practicing statisticians in academia, industry, and government could benefit from the presentation of such important and yet frequently overlooked topics.

Reviews

"… a useful addition to the ROC literature, which will prove valuable for both those involved in medical diagnosis and those whose primary interest is ROC analysis itself."

—David J. Hand, International Statistical Review (2013), 81, 2

"This new book by Zou et al significantly contributes to the existing publications by providing short descriptions on basic issues and in-depth presentations on a few advanced, research-related issues. … the interested researcher can get inspired reading this book and discover new, unexplored research paths. Another pro of the book, useful for the interested researcher, is the extensive reference list at the end of each chapter. Overall, the book by Zou et al is a valuable starting point for those conducting basic research on ROC analysis and for applied researchers who are intrigued by the use of neat methodologies in applications."

ISCB News, June 2012

Contents

Introduction

Background and Introduction

Background Information

Gold Standard, Decision Threshold, Sensitivity, and Specificity

Kappa Statistics

Receiver Operating Characteristic Curve

Area and Partial Area under ROC Curve

Confidence Intervals, Regions, and Bands

Point of Intersection and Youden Index

Comparison of Two or More ROC Curves

Approaches to ROC Analysis

References

Methods for Univariate and Multivariate Data

Diagnostic Rating Scales

Introduction

Interpreter-Free Diagnostic Systems.

Human Interpreter as Integral Part of Diagnostic System

Remarks and Further Reading.

References

Monotone Transformation Models

Introduction

General Assumptions

Empirical Methods

Nonparametric Kernel Smoothing

Parametric Models and Monotone Transformations to Binormal Distributions

Confidence Intervals

Concordance Measures in Presence of Monotone Transformations

Intraclass Correlation Coefficient

Remarks and Further Reading

References

Combination and Pooling of Biomarkers

Introduction

Combining Biomarkers to Improve Diagnostic Accuracy

ROC Curve Analysis with Pooled Samples

Remarks and Further Reading

References

Bayesian ROC Methods

Introduction

Methods for Sensitivity, Specificity, and Prevalence

Clustered Data Structures and Hierarchical Methods

Assumptions and Models for ROC Analysis

Normality Transformation

Elicitation of Prior Information

Estimation of ROC Parameters and Characteristics

Remarks and Further Reading

References

Advanced Approaches and Applications

Sequential Designs of ROC Experiments

Introduction

Group Sequential Tests Using Large Sample Theory

Sequential Evaluation of Single ROC Curve

Sequential Comparison of Two ROC Curves

Sequential Evaluation of Binary Outcomes

Sample Size Estimation

Remarks and Further Reading

References

Multireader ROC Analysis

Introduction

Overall ROC Curve and Its AUC

Statistical Analysis of Cross-Correlated Multireader Data

Remarks and Further Reading

References

Appendix 7.A: Closed Form Formulation of DBM Approach for Comparing Two Modalities Using Empirical AUC

Appendix 7.B: Variance Estimators of Empirical AUCs

Free-Response ROC Analysis

Introduction

FROC Approach

Other Approaches of Detection–Localization Performance Assessment Remarks and Further Reading References

Machine Learning and Predictive Modeling

Introduction

Predictive Modeling

Cross-Validation

Bootstrap Resampling Methods

Overfitting and False Discovery Rate

Remarks and Further Reading

References

Discussions and Extensions

Summary and Challenges

Summary and Discussion

Future Directions in ROC Analysis

Future Directions in Reliability Analysis

Final Remarks

Appendix: Notation List

Index

Name: Statistical Evaluation of Diagnostic Performance: Topics in ROC Analysis (Hardback)Chapman and Hall/CRC 
Description: By Kelly H. Zou, Aiyi Liu, Andriy I. Bandos, Lucila Ohno-Machado, Howard E. Rockette. Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (ROC) analysis in particular are important for assessing the performance of medical tests and statistical classifiers, as well as for evaluating predictive...
Categories: Drug Design & Development, Biomedical Engineering, Statistical Theory & Methods, Statistics for the Biological Sciences