Abstract Number:
3781
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Paper
Participants:
Jeffrey Albert (1), Jang Ik Cho (2), Carly Rose (1)
Institutions:
(1) Case Western Reserve University, N/A, (2) N/A, N/A
Co-Author(s):
First Author:
Presenting Author:
Abstract Text:
Causal mediation analysis seeks to decompose a treatment or exposure effect into direct and indirect effects. Initially developed for a single mediator, this methodology has been extended to allow for multiple contemporaneous or causally ordered mediators. Generalized causal mediation and path analysis (GCMPA) provides a further extension by accommodating multiple mediators at each of two causally-ordered 'stages' with mediators and the final outcome following generalized linear models. As these methods rely on the untestable assumption of sequential ignorability, a sensitivity analysis is widely considered to be an important accompaniment to causal mediation analysis. Unfortunately, methods for sensitivity analysis are currently available only for the single mediation case. We present a new sensitivity analysis approach applicable to the GCMPA setting, thus, evaluating the effect of departures from sequential ignorability on estimated path-specific effects. We discuss implementation of this methodology in the recently developed GMediation R package, and illustrate using data from a study of causal pathways between socioeconomic status and adolescent dental caries.
Keywords:
causal inference|generalized linear models|path-specific effects|sequential ignorability| |
Sponsors:
Biometrics Section
Tracks:
Longitudinal/Correlated Data
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