10–13 June 2025 | Boston, MA
Attending from StataCorp: Chuck Huber, Director, Statistical Outreach
StataCorp will be an exhibitor at the 2025 SER Conference. View downloadable copies of our flyers, and visit the 2025 SER Conference page for more information about the meeting.
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2025 SER Conference
Causal mediation analysis using Stata
Instructor: Chuck Huber, Director, Statistical Outreach
In person:
Virtual:
Fee: $55 to $180
Causal inference studies are designed to identify and quantify the effect of a treatment (T) on an outcome of interest (Y). Sometimes, the treatment has an effect on a third variable, called a mediating variable (M), which also influences the outcome. So the treatment may have both a direct effect on the outcome (T -> Y) and an indirect effect on the outcome through its influence on the mediating variable (T -> M -> Y). The goal of causal mediation analysis is to identify and quantify these direct and indirect effects. This talk will introduce the concepts and jargon of causal mediation analysis, demonstrate how to analyze these kinds of data using Stata's mediate command, and show how to interpret and visualize these kinds of relationships. [Read more ...]
Registration
Chuck Huber
Director, Statistical Outreach
Chuck Huber is Director of Statistical Outreach at StataCorp LLC and Adjunct Associate Professor of Biostatistics at the Texas A&M School of Public Health and at the New York University School of Global Public Health. In addition to working with Stata's team of software developers, he produces instructional videos for the Stata YouTube channel, writes blog entries, develops online NetCourses, and gives talks about Stata at conferences and universities. Most of his current work is focused on statistical methods used by behavioral and health scientists. He has published in the areas of neurology, human and animal genetics, alcohol and drug abuse prevention, nutrition, and birth defects. Dr. Huber currently teaches survey sampling at NYU and introductory biostatistics at Texas A&M, where he previously taught categorical data analysis, survey data analysis, and statistical genetics.
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