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Statistical Estimation of Epidemiological Risk (Statistics in Practice)
 
 
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Statistical Estimation of Epidemiological Risk (Statistics in Practice) [Hardcover]

Kung-Jong Lui (Author)

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Book Description

March 22, 2004 047085071X 978-0470850718 1
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.

Other key features include:

  • Provides comprehensive coverage of the key epidemiological indices.
  • Includes coverage of various sampling methods, and pointers to where each should be used.
  • Includes up-to-date references and recent developments in the field.
  • Features many real examples, emphasising the practical nature of the book.
  • Each chapter is self-contained, allowing the book to be used as a useful reference source.
  • Includes exercises, enabling use as a course text.

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Editorial Reviews

Review

"…a concise, organized, and well-written text that provides the derivations of statistical formulas underlying much epidemiological research and practice." (Journal of the American Statistical Association, December 2005)

"...presents a considerable amount of recent research, much of which is the author's own..." (Royal Statistical Society, Vol.168, No.1, January 2005)

"...systematically organised...an excellent reference..." (Short Book Review, Vol.24, No.3 December 2004)

"...this book is strongly recommended..." (Statistical Methods in Medical Research, Vol 14 2005)

From the Back Cover

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. 
  • 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 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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Inside This Book (learn more)
First Sentence:
To quantify the impact of a given disease on public health in a community. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
binomial sampling procedures, using interval estimators, independent cluster sampling, traditional intraclass, asymptotic interval estimators, hoc adjustment procedure, interval estimate for the intraclass, cluster randomization trials, sth stratum, independent binomial sampling, underlying disease rate, estimated asymptotic variance, patient receiving surgery, inflammation grade, dichotomous exposure, independent negative binomial, asymptotic likelihood ratio test, using the delta method, sampled subjects, percent confidence region, conditional confidence interval, percent confidence interval, following quadratic equation, joint probability mass function, trinomial distribution
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Monte Carlo, Preventive Medicine, Cancer Research, Cases Controls, Categorical Data Analysis, Continuous Univariate Distributions, Oxford University Press, Duxbury Press, Journal of Chronic Diseases, Journal of the American Medical Association, Journal of the American Statistical Association
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