© 2014 – Chapman and Hall/CRC
898 pages | 157 B/W Illus.
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 Edition
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.
A wealth of supporting material can be downloaded from the book’s CRC Press web page, including:
"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 2014
Praise 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
What is Epidemiology?
Case Studies: The Work of Doll and Hill
Populations and Samples
Measuring the Risk Factor
Studies Using Routine Data
BASIC ANALYTICAL PROCEDURES
Types of Variables
Tables and Charts
Inferential Techniques for Categorical Variables
Descriptive Techniques for Quantitative Variables
Inferences about Means
Inferential Techniques for Non-Normal Data
Assessing Diagnostic Tests
ASSESSING RISK FACTORS
Risk and Relative Risk
Odds and Odds Ratio
Relative Risk or Odds Ratio?
Risk Factors Measured at Several Levels
Rate and Relative Rate
Measures of Difference
EPITAB Commands in Stata
CONFOUNDING AND INTERACTION
The Concept of Confounding
Identification of Confounders
The Concept of Interaction
Testing for Interaction
Dealing with Interaction
EPITAB Commands in Stata
Cohort Life Tables
Comparison of Two Sets of Survival Probabilities
The Person-Years Method
Basic Design Concepts
Basic Methods of Analysis
Selection of Cases
Selection of Controls
The Analysis of Matched Studies
Nested Case-Control Studies
Avoidance of Bias
Parallel Group Studies
Allocation to Treatment Group
Trials as Cohorts
SAMPLE SIZE DETERMINATION
Testing a Mean Value
Testing a Difference between Means
Testing a Proportion
Testing a Relative Risk
Complex Sampling Designs
MODELING QUANTITATIVE OUTCOME VARIABLES
One Categorical Explanatory Variable
One Quantitative Explanatory Variable
Two Categorical Explanatory Variables
General Linear Models
Several Explanatory Variables
MODELING BINARY OUTCOME DATA
Problems with Standard Regression Models
Interpretation of Logistic Regression Coefficients
Multiple Logistic Regression Models
Tests of Hypotheses
Dealing with a Quantitative Explanatory Variable
Outcomes with Several Levels
MODELING FOLLOW-UP DATA
Basic Functions of Survival Time
Estimating the Hazard Function
Proportional Hazards Regression Models
The Cox Proportional Hazards Model
The Weibull Proportional Hazards Model
Pooled Logistic Regression
A General Approach to Pooling
Pooling Tabular Data
Individual Participant Data
Dealing with Aspects of Study Quality
Advantages and Limitations of Meta-Analysis
RISK SCORES AND CLINICAL DECISION RULES
Association and Prognosis
Risk Scores from Statistical Models
The Accuracy of Predictions
Assessing an Extraneous Prognostic Variable
Presentation of Risk Scores
Bootstrap Confidence Intervals
Practical Issues When Bootstrapping
Further Examples of Bootstrapping
Bootstrap Hypothesis Testing
Limitations of Bootstrapping
Naive Imputation Methods
Univariate Multiple Imputation
Multivariate Multiple Imputation
When Is It Worth Imputing?
Appendix A: Materials Available on the Website for This Book
Appendix B: Statistical Tables
Appendix C: Additional Data Sets for Exercises