On Partial Identification of the Natural Indirect Effect.

J Causal Inference

Departments of Biostatistics and Epidemiology, Harvard School of Public Health, Boston, MA 02115.

Published: September 2017

In causal mediation analysis, nonparametric identification of the natural indirect effect typically relies on, in addition to no unobserved pre-exposure confounding, fundamental assumptions of (i) so-called "cross-world-countterfactuals" independence and (ii) no exposure-induced confounding. When the mediator is binary, bounds for partial identification have been given when neither assumption is made, or alternatively when assuming only (ii). We extend existing bounds to the case of a polytomous mediator, and provide bounds for the case assuming only (i). We apply these bounds to data from the Harvard PEPFAR program in Nigeria, where we evaluate the extent to which the effects of antiretroviral therapy on virological failure are mediated by a patient's adherence, and show that inference on this effect is somewhat sensitive to model assumptions.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11221779PMC
http://dx.doi.org/10.1515/jci-2016-0004DOI Listing

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