Quantitative bias analysis: The good, the bad and the ugly

HESI Global’s Environmental Epidemiology Committee, in collaboration with the Special Interest Group of the International Society of Environmental Epidemiology on Quantitative Bias Analysis, is excited to launch a new webinar series on Quantitative Bias Analysis (QBA), an essential tool for addressing bias in epidemiologic studies and improve risk assessment and decision making.

The first webinar in the series will feature Dr. Tim Lash (Rollins School of Public Health, Emory University), on October 28 at 11:00 AM Eastern Time. Through his presentation titled “Quantitative bias analysis: The good, the bad and the ugly”, Dr. Lash will introduce the fundamentals of various QBA methods, their utility, shortcomings, and how they are sometimes used (intentionally or unintentionally) against their best purposes.

If you are interested in learning about QBA, whether you are entirely new to the topic or looking to strengthen your foundation, this series will be of great value, and this first session is the perfect place to start.

We look forward to your participation in this exciting new series!

Abstract:
Quantitative bias analysis encompasses all methods used to estimate the direction, magnitude, and uncertainty from non-randomized research. Many of these methods have been well known for decades, but are still not routinely implemented. This talk will review the methods, their utility, where there are shortcomings, and how they are sometimes used (intentionally or unintentionally) against their best purposes.

Bio:
Timothy L. Lash is the O. Wayne Rollins Distinguished Professor of Epidemiology and Chair of the Department of Epidemiology at Emory University’s Rollins School of Public Health, and Associate Director of Population Science at Emory’s Winship Cancer Institute. His research focuses on predictive and prognostic markers of breast, prostate, and colorectal cancer recurrence. His longstanding collaborations in Denmark have involved multiple projects to study molecular markers of recurrence and to study whether concomitant use of prescription drugs affect recurrence risk. He is currently funded by the US NCI to begin adding recurrence data to the Georgia Cancer Registry. Dr. Lash’s methodological interest focuses on developing and implementing methods to quantify the influence of systematic errors on epidemiologic research. Funding from the National Library of Medicine supports his work to develop methods that quantify the influence of systematic errors on the reproducibility of epidemiologic study results. He teaches a course on quantitative bias analysis and leads the doctoral students’ journal club. He is Editor-in-Chief of EPIDEMIOLOGY, a leading general interest epidemiology journal, and coauthor of multiple editions of two epidemiology textbooks: Applying Quantitative Bias Analysis to Epidemiologic Research, 2nd edition and Modern Epidemiology, 4th edition.