Online Program Home
My Program

Abstract Details

Activity Number: 614 - Statistical Methods for Longitudinal and Other Dependent Data
Type: Contributed
Date/Time: Thursday, August 1, 2019 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics
Abstract #305118 Presentation
Title: Estimation and Inference for the Mediation Effect in a Time-Varying Mediation Model
Author(s): Xizhen Cai* and Donna L. Coffman and Megan Piper and Runze Li
Companies: Williams College and Temple University and University of Wisconsin and Penn State University
Keywords: time-varying mediation effect; point-wise confidence interval; multivariate delta method
Abstract:

Traditional mediation analysis typically examines the relations among an intervention, a time-invariant mediator, and a time-invariant outcome variable. Although there may be a direct effect of the intervention on the outcome, there is a need to understand the process by which the intervention affects the outcome. This indirect effect is frequently assumed to be time-invariant. With improvements in data collection technology, it is possible to obtain repeated assessments over time resulting in intensive longitudinal data. This calls for an extension of traditional mediation analysis to incorporate time-varying variables as well as time-varying effects. In this talk, we present our proposal of estimating and making inferences for the time-varying mediation effect; that is, a mediation effect that can vary as a function of time. Specifically, we derived the standard error formula and construct the corresponding point-wise confidence band for the time-varying mediation effect. Simulation studies show good performance when comparing the confidence band and the true underlying model. We also apply the proposed procedure to a smoking cessation study.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2019 program