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Sensitivity Analysis for Causal Mediation and Path Analysis with the GMediation R Package

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):

Jang Ik Cho  
N/A
Carly Rose  
Case Western Reserve University

First Author:

Jeffrey Albert  
Case Western Reserve University

Presenting Author:

Jeffrey Albert  
Case Western Reserve University

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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