Synopses & Reviews
This book describes statistical concepts and techniques for evaluating medical diagnostic tests and biomarkers for detecting disease. More generally, the techniques pertain to the statistical classification problem for predicting a dichotomous outcome. Measures for quantifying test accuracy are described including sensitivity, specificity, predictive values, diagnostic likelihood ratios and the Receiver Operating Characteristic Curve that is commonly used for continuous and ordinal valued tests. Statistical procedures are presented for estimating and comparing them. Regression frameworks for assessing factors that influence test accuracy and for comparing tests while adjusting for such factors are presented. This book presents many worked examples of real data and should be of interest to practicing statisticians or quantitative researchers involved in the development of tests for classification or prediction in medicine.
Review
"...[T]his is a timely book that appears to cover a gap in the existing literature...This book is well written."--Journal of the American Statistical Association
Table of Contents
1. Introduction
2. Measures of Accuracy for Binary Tests
3. Comparing Binary Tests and Regression Analysis
4. The Receiver Operating Characteristic Curve
5. Estimating the ROC Curve
6. Covariate Effects on Continuous and Ordinal Tests
7. Incomplete Data and Imperfect Reference Tests
8. Study Design and Hypothesis Testing
9. More Topics and Conclusions
References/Bibliography
Index