Statistical Estimation of Epidemiological Risk provides coverage of the most important epidemiological indices, and includes recent developments in the field. A useful reference source for biostatisticians and epidemiologists working in disease prevention, as the chapters are self-contained and feature numerous real examples. It has been written at a level suitable for public health professionals with a limited knowledge of statistics.
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KUNG-JONG LUI is a professor in the Department of Mathematics and Statistics at San Diego State University. Since he obtained his Ph.D. in biostatistics from UCLA in 1982, he has published more than 100 papers in peer-reviewed journals, including Biometrics, Statistics in Medicine, Biometrical Journal, Psychometrika, Communications in Statistics: Theory and Methods, Science, Proceedings of National Academy of Sciences, Controlled Clinical Trials, Journal of Official Statistics, IEEE Transactions on Reliability, Environmetrics, Test, Computational Statistics and Data Analysis, American Journal of Epidemiology, American Journal of Public Health, etc. He is a Fellow of the American Statistical Association, a life member of the International Chinese Statistical Association, and a member of the Western North American Region of the International Biometric Society.
Statistical estimation of indices for measuring risk is a key topic in epidemiology. A good estimator, that is unbiased and efficient, can help investigators search for the possible causes of disease. Good use of statistical methods can enable public health administrators to confidently allocate their limited resources to the appropriate methods of prevention and treatment. Statistical Estimation of Epidemiological Risk presents the most-commonly used measures of risk, and adopts a practical approach using many real and numerical examples to support the methodology.
Statistical Estimation of Epidemiological Risk is both a useful practical reference for researchers from biostatistics and epidemiology, and an accessible textbook for graduate students studying epidemiological risk. The range of examples and exercises are of great practical benefit to public health professionals working in disease prevention and control, and set this book apart from others on the topic.
Statistical estimation of indices for measuring risk is a key topic in epidemiology. A good estimator, that is unbiased and efficient, can help investigators search for the possible causes of disease. Good use of statistical methods can enable public health administrators to confidently allocate their limited resources to the appropriate methods of prevention and treatment. Statistical Estimation of Epidemiological Risk presents the most-commonly used measures of risk, and adopts a practical approach using many real and numerical examples to support the methodology.
Statistical Estimation of Epidemiological Risk is both a useful practical reference for researchers from biostatistics and epidemiology, and an accessible textbook for graduate students studying epidemiological risk. The range of examples and exercises are of great practical benefit to public health professionals working in disease prevention and control, and set this book apart from others on the topic.
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