Epidemiology : study design and data analysis / Mark Woodward

"A Chapman & Hall book."

Includes bibliographical references (pages 799-819) and index.

Table of contents Machine generated contents note: 1.1. What is epidemiology?
1.2. Case studies: the work of Doll and Hill
1.3. Populations and samples
1.3.1. Populations
1.3.2. Samples
1.4. Measuring disease
1.4.1. Incidence and prevalence
1.5. Measuring the risk factor
1.6. Causality
1.6.1. Association
1.6.2. Problems with establishing causality
1.6.3. Principles of causality
1.7. Studies using routine data
1.7.1. Ecological data
1.7.2. National sources of data on disease
1.7.3. National sources of data on risk factors
1.7.4. International data
1.8. Study design
1.8.1. Intervention studies
1.8.2. Observational studies
1.9. Data analysis

"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 "--

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