Examining the role of unmeasured confounding in mediation analysis with genetic and genomic applications.

View Abstract

BACKGROUND

In mediation analysis if unmeasured confounding is present, the estimates for the direct and mediated effects may be over or under estimated. Most methods for the sensitivity analysis of unmeasured confounding in mediation have focused on the mediator-outcome relationship.

RESULTS

The Umediation R package enables the user to simulate unmeasured confounding of the exposure-mediator, exposure-outcome, and mediator-outcome relationships in order to see how the results of the mediation analysis would change in the presence of unmeasured confounding. We apply the Umediation package to the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study to examine the role of unmeasured confounding due to population stratification on the effect of a single nucleotide polymorphism (SNP) in the CHRNA5/3/B4 locus on pulmonary function decline as mediated by cigarette smoking.

CONCLUSIONS

Umediation is a flexible R package that examines the role of unmeasured confounding in mediation analysis allowing for normally distributed or Bernoulli distributed exposures, outcomes, mediators, measured confounders, and unmeasured confounders. Umediation also accommodates multiple measured confounders, multiple unmeasured confounders, and allows for a mediator-exposure interaction on the outcome. Umediation is available as an R package at https://github.com/SharonLutz/Umediation A tutorial on how to install and use the Umediation package is available in the Additional file 1.

Investigators
Abbreviation
BMC Bioinformatics
Publication Date
2017-07-19
Volume
18
Issue
1
Page Numbers
344
Pubmed ID
28724417
Medium
Electronic
Full Title
Examining the role of unmeasured confounding in mediation analysis with genetic and genomic applications.
Authors
Lutz SM, Thwing A, Schmiege S, Kroehl M, Baker CD, Starling AP, Hokanson JE, Ghosh D