Causal mediation analysis using Stata

Chuck Huber
Additional contact information
Chuck Huber: StataCorp LLC

Oceania Stata Conference 2025 from Stata Users Group

Abstract: 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.

References: Add references at CitEc
Citations:

Downloads: (external link)
http://repec.org/osug2025/Oceania25_Huber.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:boc:osug25:6

Access Statistics for this paper

More papers in Oceania Stata Conference 2025 from Stata Users Group Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().