Description of Signal Detection for Medical Scientists: Likelihood Ratio Test-based Methodology
Signal Detection for Medical Scientists: Likelihood Ratio Based Test-Based Methodology presents the data mining techniques with focus on likelihood ratio test (LRT) based methods for signal detection. It emphasizes computational aspect of LRT methodology and is pertinent for first-time researchers and graduate students venturing into this interesting field.
The book is written as a reference book for professionals in pharmaceutical industry, manufactures of medical devices, and regulatory agencies. The book deals with the signal detection in drug/device evaluation, which is important in the post-market evaluation of medical products, and in the pre-market signal detection during clinical trials for monitoring procedures.
It should also appeal to academic researchers, and faculty members in mathematics, statistics, biostatistics, data science, pharmacology, engineering, epidemiology, and public health. Therefore, this book is well suited for both research and teaching.
- Includes a balanced discussion of art of data structure, issues in signal detection, statistical methods and analytics, and implementation of the methods.
- Provides a comprehensive summary of the LRT methods for signal detection including the basic theory and extensions for varying datasets that may be large post-market data or pre-market clinical trial data.
- Contains details of scientific background, statistical methods, and associated algorithms that a reader can quickly master the materials and apply methods in the book on one’s own problems
About the Author
Ram C. Tiwari, Ph.D. is the Director for Division of Biostatistics, CDRH, since 2016. He joined FDA in April 2008 as Associate Director for Statistical Science and Policy in the Immediate Office, Office of Biostatistics, CDER. Prior to joining FDA, he served as Program Director and Mathematical Statistician in the Division of Cancer Control and Population Sciences at National Cancer Institute, NIH; and as Professor and Chair, Department of Mathematics, University of North Carolina at Charlotte.
Dr. Jyoti Zalkikar is in the Office of Biostatistics at the Food and Drug Administration (FDA)’s Center for Drug Evaluation and Research (CDER). Her team supports the Division of Imaging and Radiation Medicine in CDER’s Office of New Drugs. Dr. Zalkikar received her PhD in Mathematics (with Statistics track) from the University of California at Santa Barbara in 1988.
Dr. Lan Huang received her Ph.D. in Statistics from University of Connecticut in 2004. From 2004 to 2009, Dr. Huang worked on cancer surveillance at national cancer institute (NCI). Dr. Huang joined FDA in 2009 as a statistical reviewer.