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On relation between separable indirect effect, natural indirect effect, and interventional indirect effect

Published 5 Jul 2025 in stat.ME | (2507.03879v1)

Abstract: Recently, the separable indirect effect (SIE) has gained attention due to its identifiability without requiring the untestable cross-world assumption necessary for the natural indirect effect (NIE). This article systematically compares the causal assumptions underlying the SIE, NIE, and interventional indirect effect (IIE) and evaluates their feasibility for mediational interpretation using the mediation null criterion, with a particular focus on the SIE. We demonstrate that, in the absence of intermediate confounders, the SIE lacks a mediational interpretation unless additional unverifiable assumptions are imposed. When intermediate confounders are present, separable effect methods fail to accurately capture the indirect effect, whereas the NIE still satisfy the mediation null criterion. Additionally, we present a new identification result for the NIE in the presence of intermediate confounders. Finally, we propose an integrated framework for practical analysis. This article emphasizes that the NIE is the most fundamental definition of indirect effect among the three measures and highlights the trade-off between mediational interpretability and assumption falsifiability.

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