Cross-direct effects in settings with two mediators

Author:

Gabriel Erin E1ORCID,Sjölander Arvid2ORCID,Follmann Dean3,Sachs Michael C4ORCID

Affiliation:

1. Section of Biostatistics, Department of Public Health, University of Copenhagen , Øster Farimagsgade 5, 1353 Køpenhavn, Denmark

2. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet , Nobels väg 12A, Stockholm 17177, Sweden

3. Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases , Bethesda, 5601 Fishers Lane, Rockville, MD 20892, USA

4. Section of Biostatistics, Department of Public Health, University of Copenhagen , Copenhagen, Denmark

Abstract

Summary When multiple mediators are present, there are additional effects that may be of interest beyond the well-known natural (NDE) and controlled direct effects (CDE). These effects cross the type of control on the mediators, setting one to a constant level and one to its natural level, which differs across subjects. We introduce five such estimands for the cross-CDE and -NDE when two mediators are measured. We consider both the scenario where one mediator is influenced by the other, referred to as sequential mediators, and the scenario where the mediators do not influence each other. Such estimands may be of interest in immunology, as we discuss in relation to measured immunological responses to SARS-CoV-2 vaccination. We provide identifying expressions for the estimands in observational settings where there is no residual confounding, and where intervention, outcome, and mediators are of arbitrary type. We further provide tight symbolic bounds for the estimands in randomized settings where there may be residual confounding of the outcome and mediator relationship and all measured variables are binary.

Funder

Swedish Research Council

Publisher

Oxford University Press (OUP)

Subject

Statistics, Probability and Uncertainty,General Medicine,Statistics and Probability

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