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Survival mediation analysis with the death‐truncated mediator: The completeness of the survival mediation parameter
Author(s) -
Tai AnShun,
Tsai ChunAn,
Lin ShengHsuan
Publication year - 2021
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.9008
Subject(s) - mediation , completeness (order theory) , truncation (statistics) , survival analysis , outcome (game theory) , mediator , proportional hazards model , causal inference , econometrics , medicine , statistics , mathematics , mathematical analysis , mathematical economics , political science , law
Abstract In medical research, the development of mediation analysis with a survival outcome has facilitated investigation into causal mechanisms. However, studies have not discussed the death‐truncation problem for mediators, the problem being that conventional mediation parameters cannot be well defined in the presence of a truncated mediator. In the present study, we systematically defined the completeness of causal effects to uncover the gap, in conventional causal definitions, between the survival and nonsurvival settings. We propose a novel approach to redefining natural direct and indirect effects, which are generalized forms of conventional causal effects for survival outcomes. Furthermore, we developed three statistical methods for the binary outcome of survival status and formulated a Cox model for survival time. We performed simulations to demonstrate that the proposed methods are unbiased and robust. We also applied the proposed method to explore the effect of hepatitis C virus infection on mortality, as mediated through hepatitis B viral load.