Statistical Estimation of Epidemiological Risk
By (author) Kung-Jong Lui
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Statistical Estimation of Epidemiological Risk by Kung-Jong Lui
Book DescriptionStatistical 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. Presents a practical overview of the key measures of epidemiological risk. Features coverage of various sampling methods, and pointers to where each should be used. Each measure discussed is supported by a number of real and numerical examples that highlight their practical use. Each chapter is self-contained, allowing the book to be used as a reference source. Includes an abundance of exercises, which give the reader a clearer understanding of the theory. Suitable for epidemiologists and public health professionals with a modest statistical background. Statistical Estimation of Epidemiological Risk is both a useful pra
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Book DetailsISBN: 9780470850718
(237mm x 164mm x 18mm)
Imprint: John Wiley & Sons Ltd
Publisher: John Wiley and Sons Ltd
Publish Date: 29-Jan-2004
Country of Publication: United Kingdom
Books By Author Kung-Jong Lui
Crossover Designs, Hardback (October 2016)
A comprehensive and practical resource for analyses of crossover designs For ethical reasons, it is vital to keep the number of patients in a clinical trial as low as possible.
Binary Data Analysis of Randomized Clinical Trials with Noncompliance, Hardback (March 2011)» View all books by Kung-Jong Lui
This book provides a systematic and organized approach to analyzing data for a RCT with noncompliance under the most frequently-encountered situations, including parallel sampling, stratified sampling, cluster sampling, parallel sampling with subsequent missing outcomes, and a series of dependent binomial sampling for repeated measurements.
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Author Biography - Kung-Jong Lui
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.
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