Krzanowski / Hand ROC Curves for Continuous Data

1. Auflage 2009
ISBN: 978-1-4398-0022-5
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 232 Seiten

Reihe: Chapman & Hall/CRC Monographs on Statistics & Applied Probability

Since ROC curves have become ubiquitous in many application areas, the various advances have been scattered across disparate articles and texts. ROC Curves for Continuous Data is the first book solely devoted to the subject, bringing together all the relevant material to provide a clear understanding of how to analyze ROC curves.
The fundamental theory of ROC curves
The book first discusses the relationship between the ROC curve and numerous performance measures and then extends the theory into practice by describing how ROC curves are estimated. Further building on the theory, the authors present statistical tests for ROC curves and their summary statistics. They consider the impact of covariates on ROC curves, examine the important special problem of comparing two ROC curves, and cover Bayesian methods for ROC analysis.
Special topics
The text then moves on to extensions of the basic analysis to cope with more complex situations, such as the combination of multiple ROC curves and problems induced by the presence of more than two classes. Focusing on design and interpretation issues, it covers missing data, verification bias, sample size determination, the design of ROC studies, and the choice of optimum threshold from the ROC curve. The final chapter explores applications that not only illustrate some of the techniques but also demonstrate the very wide applicability of these techniques across different disciplines.

With nearly 5,000 articles published to date relating to ROC analysis, the explosive interest in ROC curves and their analysis will continue in the foreseeable future. Embracing this growth of interest, this timely book will undoubtedly guide present and future users of ROC analysis.

Zielgruppe

Researchers in diagnostic medicine, machine learning, biosciences, and atmospheric sciences, psychologists concerned with tests and test development, bankers and credit people working in the personal banking sector.

Autoren/Hrsg.

Krzanowski, Wojtek J.

Hand, David J.

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Naturwissenschaften Biowissenschaften Biowissenschaften
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik

Inhaltsverzeichnis

Introduction
Background
Classification
Classifier performance assessment
The ROC curve
Population ROC Curves
Introduction
The ROC curve
Slope of the ROC curve and optimality results
Summary indices of the ROC curve
The binormal model

Estimation
Introduction
Preliminaries: classification rule and error rates
Estimation of ROC curves
Sampling properties and confidence intervals
Estimating summary indices

Further Inference on Single Curves
Introduction
Tests of separation of P and N population scores
Sample size calculations
Errors in measurements
ROC Curves and Covariates
Introduction
Covariate adjustment of the ROC curve
Covariate adjustment of summary statistics
Incremental value
Matching in case-control studies

Comparing ROC Curves
Introduction
Comparing summary statistics of two ROC curves
Comparing AUCs for two ROC curves
Comparing entire curves
Identifying where ROC curves differ

Bayesian Methods
Introduction
General ROC analysis
Meta-analysis
Uncertain or unknown group labels
Beyond the Basics
Introduction
Alternatives to ROC curves
Convex hull ROC curves
ROC curves for more than two classes
Other issues

Design and Interpretation Issues
Introduction
Missing values
Bias in ROC studies
Choice of optimum threshold
Medical imaging
Substantive Applications
Introduction
Machine learning
Atmospheric sciences
Geosciences
Biosciences
Finance
Experimental psychology
Sociology

Appendix: ROC Software
References
Further reading suggestions appear at the end of each chapter.

Über Autor(innen)

Wojtek J. Krzanowski is Emeritus Professor of Statistics at the University of Exeter and Senior Research Investigator at Imperial College. Dr. Krzanowski’s research interests include multivariate analysis, statistical modeling, classification, and computational methods. He has published 6 books, over 30 book contributions, and 100 articles in scientific journals.
David J. Hand is head of the statistics section and head of the mathematics in banking and finance program at Imperial College. Currently president of the Royal Statistical Society, Dr. Hand has been a recipient of the Guy Medal of the Royal Statistical Society, the Royal Society Wolfson Research Merit Award, and the IEEE ICDM Research Contributions Award. He has published extensively on a wide range of statistical topics.