SIGNAL DETECTION FOR MEDICAL SCIENTISTS; LIKELIHOOD RATIO TEST-BASED METHODOLOGY
Tiwari, Ram
SIGNAL DETECTION FOR MEDICAL SCIENTISTS; LIKELIHOOD RATIO TEST-BASED METHODOLOGY [electronic resource]. - BOCA RATON : CHAPMAN & HALL CRC, 2021. - 1 online resource
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. Key Features: 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
0429521928 9780429521928 9780429259753 0429259751 9780429550096 042955009X 9780429535390 0429535392
Drugs--Testing--Statistical methods.
Signal detection--Statistical methods.
Statistical hypothesis testing.
Data mining--Statistical methods.
MEDICAL / Biostatistics
MEDICAL / Pharmacology
RM301.27
615.1072/4
SIGNAL DETECTION FOR MEDICAL SCIENTISTS; LIKELIHOOD RATIO TEST-BASED METHODOLOGY [electronic resource]. - BOCA RATON : CHAPMAN & HALL CRC, 2021. - 1 online resource
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. Key Features: 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
0429521928 9780429521928 9780429259753 0429259751 9780429550096 042955009X 9780429535390 0429535392
Drugs--Testing--Statistical methods.
Signal detection--Statistical methods.
Statistical hypothesis testing.
Data mining--Statistical methods.
MEDICAL / Biostatistics
MEDICAL / Pharmacology
RM301.27
615.1072/4
