Research Method – Using Causal Diagrams for Empirical Research | Duke Kunshan University
Research Method – Using Causal Diagrams for Empirical Research
Speaker: 
Dr. John S. Ji

Assistant Professor of Environmental Health Science at Duke Kunshan University

Associate Director of international Masters of Environmental Policy (iMEP) program

Mar 20th 2018 12:00 to 13:00
Room 1079, Academic Building
Friday, August 3, 2018 - 09:45

Summary of talk:  

You often hear investigators ask: Does X have a causal effect on Y? But how do I control for other factors? In this talk, we will introduce causal diagram as a tool to draw out assumptions in studying the effects of treatments, exposures, and policy decisions. It can be used in conjunction with conventional statistical models for adjustments for confounders, measurement errors, and minimizing biases. We will describe direct acyclic graphs (DAGs), and illustrate how it is used in causal inference by showing real-world examples from the health and social science phenomenon.

Brief Biography:

Speaker: Dr. John S. Ji

Assistant Professor of Environmental Health Science at Duke Kunshan University

Associate Director of international Masters of Environmental Policy (iMEP) program

John Ji’s current research projects are in environmental health, aging, and SDGs. He was formerly the Asia and Senior Editor at The Lancet. He received his bachelor’s degree in Neuroscience from Johns Hopkins University and his doctoral degree in Environmental Health from Harvard University. Currently, he is developing a course on planetary health at DKU.