OXFORD UNIVERSITY PRESS

Epidemiology by Design: A Causal Approach to the Health Sciences

ISBN : 9780190665760

Price(incl.tax): 
¥7,689
Author: 
Daniel Westreich
Pages
240 Pages
Format
Paperback
Size
156 x 156 mm
Pub date
Nov 2019
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A (LONG OVERDUE) CAUSAL APPROACH TO INTRODUCTORY EPIDEMIOLOGY Epidemiology is recognized as the science of public health, evidence-based medicine, and comparative effectiveness research. Causal inference is the theoretical foundation underlying all of the above. No introduction to epidemiology is complete without extensive discussion of causal inference; what's missing is a textbook that takes such an approach. Epidemiology by Design takes a causal approach to the foundations of traditional introductory epidemiology. Through an organizing principle of study designs, it teaches epidemiology through modern causal inference approaches, including potential outcomes, counterfactuals, and causal identification conditions. Coverage in this textbook includes: * Introduction to measures of prevalence and incidence (survival curves, risks, rates, odds) and measures of contrast (differences, ratios); the fundamentals of causal inference; and principles of diagnostic testing, screening, and surveillance * Description of three key study designs through the lens of causal inference: randomized trials, prospective observational cohort studies, and case-control studies * Discussion of internal validity (within a sample), external validity, and population impact: the foundations of an epidemiologic approach to implementation science For first-year graduate students and advanced undergraduates in epidemiology and public health fields more broadly, Epidemiology by Design offers a rigorous foundation in epidemiologic methods and an introduction to methods and thinking in causal inference. This new textbook will serve as a foundation not just for further study of the field, but as a head start on where the field is going.

Index: 

Acknowledgements
Overview
1. Measuring Disease
2. Measures of Association
3. Causal Inference, Causal Effect Estimation, and Systematic Error
4. Diagnostic Testing, Screening, and Surveillance
5. Randomized Trials
6. Observational Cohort Studies
7. Case-Control Studies
8. Other Study Designs
9. Causal Impact, From Exposures to Interventions
Index

About the author: 

DANIEL WESTREICH received his B.S. in computer science from Yale University, and -- after a short stint as a software engineer at Microsoft -- a Ph.D. in epidemiology from the University of North Carolina, Chapel Hill. He is currently an associate professor of epidemiology at UNC, where his work focuses substantively at the intersection of HIV and women's reproductive health. He has served as a member-at-large of the executive board of the Society for Epidemiologic Research and in editorial capacities at the American Journal of Epidemiology and Epidemiology. In 2014 Dr. Westreich was awarded an NIH DP2 New Innovator Award to develop epidemiologic methods for implementation science.

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