In many health studies, researchers are interested in estimating the treatment effects on the outcome around and through an intermediate variable. Such causal mediation analyses aim to understand the mechanisms that explain the treatment effect. Although multiple mediators are often involved in real studies, most of the literature considers mediation analyses with one mediator at a time. In this article, we review some recent advances in mediation analyses when there are multiple causal pathways. We discuss the cases that (1) there is a mediator-outcome confounder that is affected by the treatment when we are interested in one mediator and (2) there are causally non-ordered multiple mediators.
CITATION STYLE
Taguri, M. (2017). Mediation analysis for multiple causal mechanisms. In Frontiers of Biostatistical Methods and Applications in Clinical Oncology (pp. 343–357). Springer Singapore. https://doi.org/10.1007/978-981-10-0126-0_21
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