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Statistics for Epidemiology





Statistics for Epidemiology
List Price: $79.95
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Manufacturer: Chapman & Hall/CRC
Written By: Nicholas P. Jewell

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Binding: Hardcover
Dewey Decimal Number: 614.40727
EAN: 9781584884330
ISBN: 1584884339
Label: Chapman & Hall/CRC
Manufacturer: Chapman & Hall/CRC
Number Of Items: 1
Number Of Pages: 352
Publication Date: 2003-08-26
Publisher: Chapman & Hall/CRC
Studio: Chapman & Hall/CRC

Editorial Reviews for Statistics for Epidemiology

Statistical ideas have been integral to the development of epidemiology and continue to provide the tools needed to interpret epidemiological studies. Although epidemiologists do not need a highly mathematical background in statistical theory to conduct and interpret such studies, they do need more than an encyclopedia of "recipes." Statistics for Epidemiology achieves just the right balance between the two approaches, building an intuitive understanding of the methods most important to practitioners and the skills to use them effectively. It develops the techniques for analyzing simple risk factors and disease data, with step-by-step extensions that include the use of binary regression. It covers the logistic regression model in detail and contrasts it with the Cox model for time-to-incidence data. The author uses a few simple case studies to guide readers from elementary analyses to more complex regression modeling. Following these examples through several chapters makes it easy to compare the interpretations that emerge from varying approaches. Written by one of the top biostatisticians in the field, Statistics for Epidemiology stands apart in its focus on interpretation and in the depth of understanding it provides. It lays the groundwork that all public health professionals, epidemiologists, and biostatisticians need to successfully design, conduct, and analyze epidemiological studies.


Consumer reviews:

Customer Rating: Average rating of 5/5Average rating of 5/5Average rating of 5/5Average rating of 5/5Average rating of 5/5
Summary: Recommended
Comment: I have to praise the author for his outstanding way of explaining even difficult epidemiological concepts. The book is very easy to read and would be suitable for the postgraduate student or even the more experienced epidemiologist. The author promises not to use any calculus, which make the book very readable. Very good book, though, the topic of survival analysis is not discussed very extensively.

Customer Rating: Average rating of 5/5Average rating of 5/5Average rating of 5/5Average rating of 5/5Average rating of 5/5
Summary: Outstanding book
Comment: This book is a hybrid, part epidemiology and part statistics. It is a resource for those that want to DO epidemiologic studies and ensure that they are performing and interpreting the statistics correctly. Jewell does all the little things right: he delivers the message in plain English, he explains thoroughly the foundations of the various epidemiologic measures of association, and he points out the pitfalls and potential misapplications of the presented statistical tools. The chapters on confounding and interaction are the clearest and the best that I have read. I endorse this book whole-heartedly



Customer Rating: Average rating of 5/5Average rating of 5/5Average rating of 5/5Average rating of 5/5Average rating of 5/5
Summary: Review
Comment: Book in new, mint condition as advertized. No hassles, no problems at all. Arrived within the projected delivery date, and shipping was free! Great, easy, reliable service. I've never had a problem buying from Amazon.

Customer Rating: Average rating of 5/5Average rating of 5/5Average rating of 5/5Average rating of 5/5Average rating of 5/5
Summary: Outstanding
Comment: I had a chance to read this book cover to cover. All I can say is "absolutely outstanding", short of calling it a historical masterpiece in the field. Very rarely do I encounter an epidemiology or biostatistic textbook that reads so well. It is optimally reader friendly; the author appears to have such a talent in explaining some most sophisticated epidemiological and statistical concepts in such a simplified language. Yet he does not sacrifice the inclusion of some very advanced epidemiological and statistical concepts. New concepts such as causal graphs and instrumental variables are also included and explained beautifully. I strongly recommend this book to all early to intermediate graduate students majoring in Epidemiology. Established epidemiologists may wish to read this book to refresh and update their knowledge. I hope the author writes more textbooks with the same style.


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