Abstract Number:
3857
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Paper
Participants:
Curtis Miller (1)
Institutions:
(1) University of New Mexico, N/A
First Author:
Presenting Author:
Abstract Text:
Mediation analysis with one exposure (X) and one outcome (Y) is fairly well
developed. When there are multiple exposures, mediators, and outcomes, there
appear to be no standard concepts or formulas.
Also, if there are multiple exposures or mediators, the effect of one exposure
on an outcome may be partially mediated by the correlation of that exposure
with other exposures; the same is true of outcomes. This means that there may
be an effect of an exposure (X) or mediator (Z) on an outcome (Y) although a
linear model for Y may indicate that X or Z is not significant as a direct
covariate.
We have developed measures of direct and indirect effects of exposures on
outcomes in the situation where there are multiple exposures, mediators, and
outcomes, and all models are linear. The measures are derived from path
analysis as developed by Wright. We demonstrate with an example based on
simulated data.
Keywords:
Mediation analysis|multiple covariates|path analysis|sparse data| |
Sponsors:
Biometrics Section
Tracks:
Miscellaneous
Can this be considered for alternate subtype?
Yes
Are you interested in volunteering to serve as a session chair?
Yes
I have read and understand that JSM participants must abide by the Participant Guidelines.
Yes
I understand that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is non-refundable.
I understand