Epidemiology: Study Design and Data Analysis 3rd Edition PDF Free Download

Highly praised for its broad, practical coverage, the second edition of this popular text incorporated the major statistical models and issues relevant to epidemiological studies. Epidemiology: Study Design and Data Analysis, Third Edition continues to focus on the quantitative aspects of epidemiological research. Updated and expanded, this edition shows students how statistical principles and techniques can help solve epidemiological problems.New to the Third EditionNew chapter on risk scores and clinical decision rules New chapter on computer-intensive methods, including the bootstrap, permutation tests, and missing value imputationNew sections on binomial regression models, competing risk, information criteria, propensity scoring, and splinesMany more exercises and examples using both Stata and SASMore than 60 new figures After introducing study design and reviewing all the standard methods, this self-contained book takes students through analytical methods for both general and specific epidemiological study designs, including cohort, case-control, and intervention studies. In addition to classical methods, it now covers modern methods that exploit the enormous power of contemporary computers. The book also addresses the problem of determining the appropriate size for a study, discusses statistical modeling in epidemiology, covers methods for comparing and summarizing the evidence from several studies, and explains how to use statistical models in risk forecasting and assessing new biomarkers. The author illustrates the techniques with numerous real-world examples and interprets results in a practical way. He also includes an extensive list of references for further reading along with exercises to reinforce understanding. Web ResourceA wealth of supporting material can be downloaded from the book’s CRC Press web page, including:Real-life data sets used in the textSAS and Stata programs used for examples in the textSAS and Stata programs for special techniques coveredSample size spreadsheet

User’s Review:

Editorial Reviews: Review “This text, like its predecessors, hits the mark. … The author writes extremely well and the text is resplendent with exercises. It would be a crime if Epidemiology: Study Design and Data Analysis were never used as a text! … I wish a text like this had been available for my coursework. Enhancing its value as a text, it will be extremely useful as a reference book for its intended audience―researchers and applied statisticians. … the only excuse for an epidemiologist or applied statistician not to have it on his or her bookshelf is that he or she has not seen or heard of it. Make this book your next purchase!”―Gregory E. Gilbert, The American Statistician, November 2014Praise for Previous Editions:”As a text in quantitative epidemiology, this book also works nicely as a text in biostatistics…The presentation style is relaxed, the examples are helpful, and the level of technical difficulty makes the material approachable without oversimplification…It is sufficiently broad and deep in coverage to compete with standard texts in the field and has the added bonus of emphasizing study design. Methods and issues related to designs commonly used in a wide variety of health sciences are included…”-Ken Hess, Department of Biomathematics and Biostatistics, Anderson Cancer Center”The second edition of this epidemiology text is strengthened to cater to the two audiences the author has in mind: applied statisticians wishing to learn how their statistical expertise can be used in the epidemiology field and statistic-curious researchers who want to understand how statistical techniques can be used to solve epidemiological problems. …The result is a book that will invariably appeal to the intended audience, one with practical applications of techniques and interpretations of results in an epidemiological context. …The book is most certainly an ambitious attempt at covering a broad array of the most important epidemiologic study designs and analytical methods. This is further enforced by the addition of the meta-analysis chapter. …This book will be valuable to statisticians in applying their discipline to epidemiology. Mark Woodward’s excellent second edition will effectively serve post-graduate or advanced undergraduate students studying epidemiology, as well as statisticians or researchers who are regularly confronted with epidemiological questions.”-Journal of the American Statistical Association”This book provides very good coverage of major issues in the design of epidemiological studies, and a decent, but very quick, tour of commonly used statistical models for such studies.”-Short Book Reviews Publication of the International Statistical Institute, K.S. Brown, University of Waterloo, Canada”Amazingly, Woodward manages to describe quite sophisticated models and analysis with nothing more complicated than summation signs. …I highly recommend it.”-Statistics in Medicine, 2006″The second edition of this concisely written book covers all statistical methods being of relevance for the planning and analysis of epidemiological studies where the author avoids unnecessary mathematical details for the sake of comprehensibility. The presented statistical principles are always carefully discussed in the context of epidemiological concepts, for instance depending on the different study designs. Detailed practical examples coming from real studies as far as possible illustrate their application. …The book can be highly recommended to researchers in epidemiology who want to understand better the statistical principles being typically applied in this field and to statisticians who want to understand more about statistics in epidemiology, but also to graduate students in epidemiology, public health, medical research and statistics.”-Biometrics, Sept. 2005″I think anyone with an interest in both biostatistics and epidemiology will want a copy this book on their bookshelf … it is a first-rate reference book.” “I find Professor Woodward’s text the most complete and practical introduction to the design and analysis of epidemiological studies I’ve encountered… an excellent text for either a course introducing epidemiologists to statistical thought and methods or a course introducing statisticians to epidemiological thought and methods… students appreciate having a readable textbook replete with understandable examples and worked exercises…offers a complete introduction to statistical and epidemiological methods in the study of disease in human populations. All of the standard topics are included, and the second edition even has a chapter on meta-analysis. …This book can be used as a text to introduce epidemiological methods to graduate students in statistics who have no background in epidemiology, or vice versa…Professor Woodward is to be congratulated on a job well done.”-Dan McGee, Dept of Statistics, Florida State University –This text refers to the hardcover edition. About the Author Mark Woodward is a professor of statistics and epidemiology at the University of Oxford, a professor of biostatistics in the George Institute at the University of Sydney, and an adjunct professor of epidemiology at Johns Hopkins University. –This text refers to the hardcover edition.

Reviews from Amazon users which were colected at the time this book was published on the website:

I am an entry-level biostatistician, I bought a book that would help me review what I learned in my MPH program. I love the book the language used is simple and gives all the details you need to become better in research. The only downside for me is that they used SAS and Stata only for data analysis I prefer R. Also, the datasets that was used in the examples are provided online, it is hard to find it and to know which dataset was used for which example. In general this book is a must to have if you work in medical research

This book is an excellent source for designing quality epidemiological research. It also directs the researcher to specific and appropriate statistical tests to apply to the data. It is a great place to start when designing an epidemiological study.

I loved this textbook. I used it for a course in my grad program called “Statistical methods in epidemiology.” Was wonderful and in perfect condition.

Excellent resource for graduate level quantitative epidemiology courses.

Bought instead of renting so I have a handy copy for future review. Great reference!

This is quite useful book to have on your shelf.It covers almost all basics with rich examples. It is a practical book with essential theory.

Good book

It’s a must have for all public health and epidemiology professionals. Especially those who use SAS or STATA statistical packages in their analysis. Not extended on multiple imputation and propensity score matching as you’d hope. Overall it covers most aspects of health related research in both concep and application.

very impressed by this- clear and detailed, without being too daunting. As someone more at ease with words than maths, I found this managed to make statistics comprehensible in a way which is rare- I’d recommend it for MSc level and above.

It was amazing

Although this text does not have the pretty layout and fancy pictures that some other epidemiology books have, it contains a wonderful wealth of information. An excellent feature of the book is that it integrates statistical analysis with epidemiology, and in my view the two are on one continuum. The sections of the text that I have read have been clearly written. I’m a professor who teaches epidemiology at the senior undergraduate and graduate level. I find that the standard much-used text by Gordis is superficial in comparison to the Woodward text. The third edition of Epidemiology: Study Design and Data Analysis includes satisfactory coverage of many recently advanced important topics, such as meta-analysis, risk scores and prediction modeling, analysis of longitudinal data, propensity scoring, use of bootstrap estimations, and multiple imputations for missing data. Although many of these seem to be advanced topics, they are introduced and developed in an approachable fashion useful even for Masters level students. This text may overwhelm undergraduate students, who are taking one course in epidemiology and who may not go on to do further studies in this area. I do recommend this text for those who are seriously interested in epidemiology and related statistical analyses, in particular, graduate students who plan to specialize in epidemiology.

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