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Introduction to Mediation Analysis and Examples of Its Application to Real-world Data

Traditional epidemiological assessments, which mainly focused on evaluating the statistical association between two major components-the exposure and outcome-have recently evolved to ascertain the in-between process, which can explain the underlying causal pathway. Mediation analysis has emerged as...

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Detalles Bibliográficos
Autor principal: Jung, Sun Jae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society for Preventive Medicine 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190553/
https://www.ncbi.nlm.nih.gov/pubmed/34092062
http://dx.doi.org/10.3961/jpmph.21.069
Descripción
Sumario:Traditional epidemiological assessments, which mainly focused on evaluating the statistical association between two major components-the exposure and outcome-have recently evolved to ascertain the in-between process, which can explain the underlying causal pathway. Mediation analysis has emerged as a compelling method to disentangle the complex nature of these pathways. The statistical method of mediation analysis has evolved from simple regression analysis to causal mediation analysis, and each amendment refined the underlying mathematical theory and required assumptions. This short guide will introduce the basic statistical framework and assumptions of both traditional and modern mediation analyses, providing examples conducted with real-world data.