The definitive resource for ensuring diagnostic tests meet the highest standards of statistical rigor and clinical effectiveness

Statistical Methods in Diagnostic Medicine, 3rd Edition by Xiao-Hua Zhou, Jiarui Sun, Gene A. Pennello, Nancy A. Obuchowski and Donna K. McClish delivers the most comprehensive treatment of statistical methodologies for diagnostic test evaluation available today. The authors of the 2^nd Edition – Peking University PKU Distinguished Chair Professor Zhou, Cleveland Clinic Professor Obuchowski, and Virginia Commonwealth University Professor Donna McClish – team with U.S. Food and Drug Administration senior mathematical statistician Pennello and doctoral researcher Sun to address a critical challenge facing medical professionals: ensuring that diagnostic tests used in clinical practice are accurate, methodologically sound, free from bias, and effective.

This edition provides practitioners and researchers with the statistical foundation necessary to design, analyze, and validate diagnostic studies that can withstand regulatory scrutiny and clinical demands. The book has been thoroughly revised to incorporate the latest advances in diagnostic test methodology, featuring significant expansions in biomarker evaluation and benefit-risk assessment. The authors have restructured content to improve cohesion through integrated case studies that span multiple chapters, while updating each section with contemporary methods and streamlining discussions of older techniques to focus on the most relevant approaches for today’s diagnostic challenges.

Readers will also find:

• Three entirely new chapters covering statistical methods for risk prediction, quantitative imaging biomarkers, and efficacy and effectiveness of biomarkers and other tests.
• Enhanced coverage of sample size calculations, accuracy estimation methods, and comparative analysis techniques for competing diagnostic tests
• Advanced analytical approaches including methods for comparing correlated ROC curves in multi-reader studies and techniques for correcting verification bias
• Comprehensive treatment of regression analysis applications in diagnostic accuracy research with updated methodological guidance
• Integrated case studies that demonstrate real-world application of statistical methods across different diagnostic scenarios and study designs

Perfect for biostatisticians, applied statisticians, clinical researchers, and regulatory professionals working in diagnostic medicine, Statistical Methods in Diagnostic Medicine will also benefit graduate students and researchers interested in gaining the statistical expertise needed to design robust diagnostic studies.

Xiao-Hua Zhou, fellow of the American Association for the Advancement of Science, fellow of the American Statistical Association, fellow of Institute of Mathematical Statistics, is PKU Distinguished Chair Professor and Chair of the Department of Biostatistics at Peking University, Beijing, China. His research focuses on statistical methods for diagnostic medicine, causal inference, and clinical trials, with extensive experience in regulatory statistics and biomedical research methodology. He has published more than 290 referred papers in those areas.

Jiarui Sun is Senior Biostatistician in Shanghai Shengdi Pharmaceutical Co., Ltd. and received his Ph.D from the School of Mathematical Science at Peking University, Beijing, China. His research interests include statistical methods for diagnostic accuracy studies, biomarker evaluation, and computational approaches to medical statistics and diagnostic test validation.

Gene A. Pennello, fellow of the American Statistical Association, is a statistical reviewer and research Mathematical Statistician at the U.S. Food and Drug Administration (FDA) in Silver Spring, Maryland. He specializes in statistical methods for medical device evaluation, diagnostic test assessment, and regulatory review processes for medical technologies.

Nancy A. Obuchowski, fellow of the American Statistical Association, Professor of Medicine at the Cleveland Clinic Lerner College of Medicine at Case Western Reserve University, has extensive experience in the design, analysis, and development of new statistical methodology for the evaluation of diagnostic and screening tests and quantitative imaging biomarkers.

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.