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Activity Number: 338
Type: Topic Contributed
Date/Time: Tuesday, August 6, 2013 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #308012
Title: The Estimation of Direct and Indirect Causal Effects in the Presence of Misclassified Binary Mediator
Author(s): Linda Valeri*+ and Tyler J VanderWeele
Companies: Harvard University and Harvard School of Public Health
Keywords: Iteratively re-weighted least squares ; maximum likelihood ; mediation analysis ; misclassification; ; predictive value weighting ; sensitivity analyses
Abstract:

Mediation analysis serves to quantify the effect of an exposure on an outcome mediated by a certain intermediate, and to quantify the extent to which the effect is direct. When the mediator is misclassified the validity of mediation analysis can be severely undermined. The contribution of the present work is to study the effects of non-differential misclassification of a binary mediator in the estimation of direct and indirect causal effects when the outcome is either continuous or binary and exposure-mediator interaction can be present, and to allow for the correction of misclassification. A full maximum likelihood approach and an hybrid of likelihood-based and predictive value weighting method for misclassification correction coupled with sensitivity analyses are proposed and compared for which no validation samples or gold standard for the misclassified mediator are needed. The approaches are applied to a perinatal epidemiological study on the determinants of pre-term birth.


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