This presentation describes mediation analysis and the connections between traditional mediation analysis and recently developed causal mediation analysis. Mediating variables have a long and important history in theoretical and applied research because they describe how and why two variables are related. One common example of applied mediation research is the study of the mediating processes that explain how a prevention/treatment program achieves its effects on an outcome variable. If the intervention’s active ingredients are identified, the intervention can be made more powerful and more efficient. Other applied mediation examples include identifying how a risk factor leads to disease and how early life experiences affect later development.

Important recent developments in causal mediation analysis include new counterfactual (potential outcomes) methods that generate accurate estimates for continuous and categorical measures. In general, researchers have been slow to adopt causal mediation methods because of their complexity and the perceived lack of connection between traditional and causal methods. However, understanding connections between traditional and causal mediation increases understanding of both methods. The background for each approach is described, along with questions about traditional mediation and potential outcomes that causal mediation perspectives can help answer. The presentation ends with future directions in mediation theory and statistical analysis.

Dr. David P. MacKinnon has been developing, evaluating, and applying methods to assess how interventions work for over 30 years. He is a Foundation Professor of Psychology at Arizona State University. He received his undergraduate degree from Harvard University, and his Ph.D. in measurement and psychometrics from UCLA in 1986. In 2011, he received the Nan Tobler Award from the Society for Prevention Research for his book on statistical mediation analysis. Dr. MacKinnon has been Principal Investigator on several National Institutes of Health grants. He received the Method to Extend Research in Time (MERIT) Award from the National Institute on Drug Abuse for his research on mediation analysis. He has given numerous workshops in the United States and Europe, has served on federal grant review committees and as a consulting editor, and is a Web of Science Highly Cited Researcher. He is a Fellow of the Association for Psychological Science, Society for Prevention Research, and American Psychological Association Quantitative and Qualitative Methods Division. He is past president of American Psychological Association Division 5 and is president-elect of the Society of Multivariate Experimental Psychology.

https://prevention.nih.gov/education-training/methods-mind-gap/connections-between-traditional-and-causal-mediation-methods?utm_source=ODPEblast&utm_medium=email&utm_campaign=MindTheGap 

Can't be there? A recording of this webinar will be available approximately 1 week after the session. You can view the full archive of previous Methods: Mind the Gap webinars on the NIH Office of Disease Prevention website.

This event is open to the public and there will be an opportunity to ask questions at the end of the presentation. Please feel free to share this information widely. For more information, please contact us at MindtheGap@od.nih.gov. 

Registration URL: https://prevention.nih.gov/education-training/methods-mind-gap/connections-between-traditional-and-causal-mediation-methods?utm_source=ODPEblast&utm_medium=email&utm_campaign=MindTheGap

The Center for the Assessment of Tobacco Regulations (CAsToR) has developed a short course on tobacco simulation modeling (EPID 730) to be offered during the University of Michigan Summer Session in Epidemiology (SSE) Program in 2020.The course, EPID 730 Simulation Modeling of Tobacco Use, Health Effects and Policy Impacts (2 credit hours), will be taught by Drs. Rafael Meza and Jihyoun Jeon on July 27-31, 2020.  The course will provide an introductory overview of computational modeling techniques with examples in Tobacco Control and Regulatory Science (TCRS), discussions of best practices, and hands-on lab experience in which students will develop their own simulation models. At the completion of the course, students will be able to explain the contributions of simulation modeling in TCRS, and describe advantages and disadvantages of common modeling approaches. Students will explore how to incorporate simulation modeling into their own TCRS research and participate in interdisciplinary teams that use modeling techniques. 

A tentative course syllabus can be viewed here: https://drive.google.com/file/d/1oSVV6LM0vv648ZR6IaJsKftlg6ElswUp/view

More information on how to apply: https://sph.umich.edu/umsse/application/index.html#online