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"Building an up-to-date understanding of the methodologies that can be used to shape public health policies, Epidemiology: Study Design and Data Analysis, Second Edition encompasses the study of epidemiology from the observation of associations between risk factors and disease to the use of practical, data-supported analyses. It presents study designs commonly used for a wide range of purposes, and covers the spectrum of statistical principles and analytical tools used in epidemiological research, such as techniques used in report writing, descriptive analyses, statistical models and synthesis of evidence. (Midwest)."
"Covers the spectrum of standard analytical techniques used in epidemiology, from the descriptive techniques used in report writing to model diagnostics from generalized linear models. The second edition incorporates new material on systematic evaluation, linear mixed models, regression dilution, case-cohort studies, genetic epidemiology, and meta-analysis."
""This book is about the quantitative aspects of epidemiological research. I have written it with two audiences in mind: the researcher who wishes to understand how statistical principles and techniques may be used to solve epidemiological problems and the applied statistician who wishes to find out how to apply her or his subject in this field. A practical approach is used; although a complete set of formulae are included where hand calculation is viable, mathematical proofs are omitted and statistical nicety has largely been avoided. The techniques described are illustrated by example, and results of the applications of the techniques are interpreted in a practical way. Sometimes hypothetical datasets have been constructed to produce clear examples of epidemiological concepts and methodology. However, the majority of the data used in examples, and exercises, are taken from real epidemiological investigations, drawn from past publications or my own collaborative research. Several substantial datasets are either listed within the book or, more often, made available on book's web site for the reader to explore using her or his own computer software. SAS and Stata programs for most of the examples, where appropriate, are also provided on this web site. Finally, an extensive list of references is included for further reading. I have assumed that the reader has some basic knowledge of statistics, such as might be obtained from a medical degree course, or a first-year course in statistics as part of a science degree. Even so, this book is self-contained in that all the standard methods necessary to the rest of the book are reviewed in Chapter 2. From this base, the text goes through analytical methods for general and specific epidemiological study designs"--Résumé de l'éditeur."
""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 "--"
""Preface This book is about the quantitative aspects of epidemiological research. I have written it with two audiences in mind: the researcher who wishes to understand how statistical principles and techniques may be used to solve epidemiological problems and the applied statistician who wishes to find out how to apply her or his subject in this field. A practical approach is used; although a complete set of formulae are included where hand calculation is viable, mathematical proofs are omitted and statistical nicety has largely been avoided. The techniques described are illustrated by example, and results of the applications of the techniques are interpreted in a practical way. Sometimes hypothetical datasets have been constructed to produce clear examples of epidemiological concepts and methodology. However, the majority of the data used in examples, and exercises, are taken from real epidemiological investigations, drawn from past publications or my own collaborative research. Several substantial datasets are either listed within the book or, more often, made available on book's web site for the reader to explore using her or his own computer software. SAS and Stata programs for most of the examples, where appropriate, are also provided on this web site. Finally, an extensive list of references is included for further reading. I have assumed that the reader has some basic knowledge of statistics, such as might be obtained from a medical degree course, or a first-year course in statistics as part of a science degree. Even so, this book is self-contained in that all the standard methods necessary to the rest of the book are reviewed in Chapter 2. From this base, the text goes through analytical methods for general and specific epidemiological study designs"--"
"""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 yo."@en
""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 "--Résumé de l'éditeur."

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