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Defining and estimating causal direct and indirect effects when setting the mediator to specific values is not feasible
Author(s) -
Lok Judith J.
Publication year - 2016
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.6990
Subject(s) - mediator , covariate , indirect effect , set (abstract data type) , outcome (game theory) , mechanism (biology) , transmission (telecommunications) , value (mathematics) , human immunodeficiency virus (hiv) , medicine , econometrics , psychology , computer science , statistics , immunology , mathematics , telecommunications , philosophy , mathematical economics , epistemology , political science , law , programming language
Natural direct and indirect effects decompose the effect of a treatment into the part that is mediated by a covariate (the mediator) and the part that is not. Their definitions rely on the concept of outcomes under treatment with the mediator ‘set’ to its value without treatment. Typically, the mechanism through which the mediator is set to this value is left unspecified, and in many applications, it may be challenging to fix the mediator to particular values for each unit or patient. Moreover, how one sets the mediator may affect the distribution of the outcome. This article introduces ‘organic’ direct and indirect effects, which can be defined and estimated without relying on setting the mediator to specific values. Organic direct and indirect effects can be applied, for example, to estimate how much of the effect of some treatments for HIV/AIDS on mother‐to‐child transmission of HIV infection is mediated by the effect of the treatment on the HIV viral load in the blood of the mother. Copyright © 2016 John Wiley & Sons, Ltd.