Statistical Methods in Diagnostic Medicine

Description

This book provides a comprehensive account of statistical methods for the design and analysis of diagnostic studies, including sample size calculations, estimation of the accuracy of a diagnostic test, comparison of accuracies of competing diagnostic tests, and regression analysis of diagnostic accuracy data. Discussing recently developed methods for correction of verification bias and imperfect reference bias, methods for analysis of clustered diagnostic accuracy data, and meta-analysis methods, the authors stress common measures of diagnostic accuracy and designs for diagnostic accuracy studies, methods of estimation and hypothesis testing of the accuracy of diagnostic tests, and advanced analytic techniques such as methods for comparing correlated ROC curves in multi-reader studies, correcting verification bias, and correcting imperfect gold standards. The book has rapidly become a valuable addition to the literature of the field, serving as a much-needed guide for both clinicians and advanced students.

Author Information

Xiao-Hua Zhou, PhD, is Professor of Biostatistics at the University of Washington and Director and Research Career Scientist at the Biostatistics Unit of the Veterans Affairs Puget Sound Healthcare System. He is a Fellow of the American Statistical Association and the author of more than 100 published articles on statistical methods in diagnostic medicine and causal inferences.

Nancy A. Obuchowski, PhD, is Vice Chairperson of the Department of Quantitative Health Sciences at the Cleveland Clinic Foundation. A Fellow of the American Statistical Association, she has written more than 100 journal articles on the design and analysis of studies of screening and diagnostic tests.

Donna K. McClish, PhD, is Associate Professor and Graduate Program Director in Biostatistics at Virginia Commonwealth University. She has written more than 100 journal articles on statistical methods in epidemiology, diagnostic medicine, and health services research.