Mathematics (Jul 2024)

Sequential Ignorability and Dismissible Treatment Components to Identify Mediation Effects

  • Yuhao Deng,
  • Haoyu Wei,
  • Xia Xiao,
  • Yuan Zhang,
  • Yuanmin Huang

DOI
https://doi.org/10.3390/math12152332
Journal volume & issue
Vol. 12, no. 15
p. 2332

Abstract

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Mediation analysis is a useful tool to study the mechanism of how a treatment exerts effects on the outcome. Classical mediation analysis requires a sequential ignorability assumption to rule out cross-world reliance of the potential outcome of interest on the counterfactual mediator in order to identify the natural direct and indirect effects. In recent years, the separable effects framework has adopted dismissible treatment components to identify the separable direct and indirect effects. In this article, we compare the sequential ignorability and dismissible treatment components for longitudinal outcomes and time-to-event outcomes with time-varying confounding and random censoring. We argue that the dismissible treatment components assumption has advantages in interpretation and identification over sequential ignorability, whereas these two conditions lead to identical estimators for the direct and indirect effects. As an illustration, we study the effect of transplant modalities on overall survival mediated by leukemia relapse in patients undergoing allogeneic stem cell transplantation. We find that Haplo-SCT reduces the risk of overall mortality through reducing the risk of relapse, and Haplo-SCT can serve as an alternative to MSDT in allogeneic stem cell transplantation.

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