Epidemiology : Study Design and Data Analysis

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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. New Material in This Edition Includes: Systematic evaluation Meta-analysis Regression dilution Case-cohort studies Case-crossover studies Pooled logistic regression Companion Web site containing data sets for examples and exercises, SAS and Stata code for examples, a sample size calculator, and a SAS floating absolute risk macro The second edition of a popular textbook, this book emphasizes quantitative and design aspects of epidemiological research. The author favors the use of basic mathematics and practical methods over complicated mathematical proofs, making this an ideal textbook that is comprehensive yet accessible to graduate students in epidemiology, statistics, public health studies, and/or medical research.show more

Product details

  • Hardback | 870 pages
  • 164 x 236 x 48mm | 1,338.11g
  • Taylor & Francis Inc
  • Chapman & Hall/CRC
  • Boca Raton, FL, United States
  • English
  • Revised
  • 2nd Revised edition
  • 125 black & white illustrations, 219 black & white tables
  • 1584884150
  • 9781584884156
  • 440,174

Review quote

"As a text in quantitative Epidemiology, this book also works nicely as a text in BiostatisticsThe presentation style is relaxed, the examples are helpful, and the level of technical difficulty makes the material approachable without oversimplificationIt 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 "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 Universityshow more

Table of contents

PREFACE FUNDAMENTAL ISSUES What is Epidemiology? Case Studies: The Work of Doll and Hill Populations and Samples Measuring Disease Measuring the Risk Factor Causality Studies Using Routine Data Study Design Data Analysis Exercises BASIC ANALYTICAL PROCEDURES Introduction Case Study 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 Measuring Agreement Assessing Diagnostic Tests Exercises ASSESSING RISK FACTORS Risk and Relative Risk Odds and Odds Ratio Relative Risk or Odds Ratio? Prevalence Studies Testing Association Risk Factors Measured at Several Levels Attributable Risk Rate and Relative Rate Measures of Difference Exercises CONFOUNDING AND INTERACTION Introduction The Concept of Confounding Identification of Confounders Assessing Confounding Standardization Mantel-Haenszel Methods The Concept of Interaction Testing for Interaction Dealing with Interaction Exercises COHORT STUDIES Design Considerations Analytical Considerations Cohort Life Tables Kaplan-Meier Estimation Comparison of Two Sets of Survival Probabilities The Person-Years Method Period-Cohort Analysis Exercises CASE-CONTROL STUDIES Basic Design Concepts Basic Methods of Analysis Selection of Cases Selection of Controls Matching The Analysis of Matched Studies Nested Case-Control Studies Case-Cohort Studies Case-Crossover Studies Exercises INTERVENTION STUDIES Introduction Ethical Considerations Avoidance of Bias Parallel Group Studies Cross-Over Studies Sequential Studies Allocation to Treatment Group Exercises SAMPLE SIZE DETERMINATION Introduction Power Testing a Mean Value Testing a Difference Between Means Testing a Proportion Testing a Relative Risk Case-Control Studies Complex Sampling Designs Concluding Remarks Exercises MODELLING QUANTITATIVE OUTCOME VARIABLES Statistical Models One Categorical Explanatory Variable One Quantitative Explanatory Variable Two Categorical Explanatory Variables Model Building General Linear Models Several Explanatory Variables Model Checking Confounding Longitudinal Data Non-Normal Alternatives Exercises MODELLING BINARY OUTCOME DATA Introduction Problems with Standard Regression Models Logistic Regression Interpretation of Logistic Regression Coefficients Generic Data Multiple Logistic Regression Models Tests of Hypotheses Confounding Interaction Model Checking Regression Dilution Case-Control Studies Outcomes with Several Ordered Levels Longitudinal Data Complex Sampling Designs Exercises MODELLING FOLLOW-UP DATA Introduction Basic Functions of Survival Time Estimating the Hazard Function Probability Models Proportional Hazards Regression Models The Cox Proportional Hazards Model The Weibull Proportional Hazards Model Model Checking Poisson Regression Pooled Logistic Regression Exercises META-ANALYSIS Reviewing Evidence Systematic Review A General Approach to Pooling Investigating Heterogeneity Pooling Tabular Data Individual Participant Data Dealing with Aspects of Study Quality Publication Bias Is Meta-Analysis a Valid Tool in Epidemiology? Exercises APPENDIX A: MATERIALS AVAILABLE FROM THE WEBSITE APPENDIX B: STATISTICAL TABLES APPENDIX C: EXAMPLE DATA SETS SOLUTIONS TO EXERCISES REFERENCES INDEXshow more

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