An introduction to causal mediation analysis

• Published in: Asia Pacific education review Vol. 25; no. 3; pp. 703 - 717
• Main Author: Qin, Xu
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.09.2024; Springer Nature B.V; 교육연구소
• Subjects: Affective Behavior; Control Groups; Dependents; Depression (Psychology); Education; Educational Research; Literature Reviews; Low Income Groups; Path Analysis; Psychological Patterns; Researchers; Review Article; Sensitivity analysis; Structural Equation Models; Wages; 교육학; Literature review; Causal; Mediation
• ISSN: 1598-1037; 1876-407X
• DOI: 10.1007/s12564-024-09962-5

Causal mediation analysis has gained increasing attention in recent years. This article guides empirical researchers through the concepts and challenges of causal mediation analysis. I first clarify the difference between traditional and causal mediation analysis and highlight the importance of adjusting for the treatment-by-mediator interaction and confounders of the treatment–mediator, treatment–outcome, and mediator–outcome relationships. I then introduce the definition of causal mediation effects under the potential outcomes framework and different methods for the identification and estimation of the effects. After that, I highlight the importance of conducting a sensitivity analysis to assess the sensitivity of analysis results to potential unmeasured confounding. I also list various statistical software that can conduct causal mediation analysis and sensitivity analysis and provide suggestions for writing a causal mediation analysis paper. Finally, I briefly introduce some extensions that I made with my colleagues, including power analysis, multisite causal mediation analysis, causal moderated mediation analysis, and relaxing the assumption of no post-treatment confounding.