Interpreting Epidemiologic Evidence: Connecting Research to Applications

By Gregory A. Wellenius, David A. Savitz, Gregory A. Wellenius

Book Overview

Epidemiology, the so-called "science of public health," has undergone a boom in the last decade as public interest and engagement in population health has skyrocketed. While this boom has done much to spark advances in the technology of epidemiology, it has also made it harder for those who want to use epidemiology to guide policy and clinical practice to fully appreciate the meaning of the research findings.

Interpreting Epidemiologic Evidence offers those who have had an introductory course in epidemiology the knowledge they need to make clear connections from research findings to practical applications. Written in clear and lively prose, it empowers students at all levels to evaluate a study's design, implementation, and ultimate findings, giving the guidance needed to apply the information appropriately. Liberal use of practical examples serves both to illustrate core concepts and to motivate readers to think critically about the causal connections that population health studies aim to explore.

Completely revised and updated, this new edition of Interpreting Epidemiologic Evidence is an invaluable core text for both epidemiologists in training and practitioners across other disciplines with even an introductory knowledge of epidemiology.

• Format: Paperback
• Language: English
• ISBN: 0190243775
• ISBN13: 9780190243777
• Release Date: July 2016
• Publisher: Oxford University Press
• Length: 240 Pages
• Weight: 0.79 lbs.
• Dimensions: 0.4" x 6.1" x 9.1"

Customer Reviews

Required reading for every epidemiologist

This book by David Savitz is an important and welcome addition to the epidemiologist's library. I started reading it after my first year of doctoral studies but I did not fully appreciate the usefulness of Dr. Savitz's insights until after I started doing independent research as a academic physician-epidemiologist. The book is well-written and presents the various methodologic challenges faced by epidemiologic researchers in a logical and coherent way. The chapter on selection bias is particularly illuminating. Remarkably, all the information is presented in lucid prose without the use of mathematical notation. If you would like to get the most out of your research endeavours, this book is for you. I think it should be required reading for every epidemiologist.