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

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.