Bayesian Dynamic Mediation Analysis

• Activity Number: 319
• Type: Contributed
• Date/Time: Tuesday, August 11, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): Jing Huang*
• Keywords: Dynamic mediation ; Multilevel mediation ; Bayesian inference ; Time-varying coecient ; Penalized spline.

Abstract

Most existing methods for mediation analysis assume that mediation is a static, time invariant process, which overlooks the inherently dynamic nature of many human psychological processes and behavioral activities. In this article, we consider mediation as a dynamic process that continuously changes over time. We propose Bayesian multilevel time-varying coefficient models to describe and estimate such dynamic mediated effects. By taking the nonparametric penalized spline approach, the proposed method is flexible and able to accommodate any shape of the relationship between time and mediated effects. Simulation studies show that the proposed method works well and faithfully reflects the true nature of the mediation process. Our method provides a valuable tool to help researchers obtain a more complete understanding of the dynamic nature of the mediation process underlying psychological and behavioral phenomena.