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Activity Number: 570 - Joint Modeling of Longitudinal and Survival Data
Type: Contributed
Date/Time: Wednesday, July 31, 2019 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #306416
Title: Joint Spline Models for Continuous Time Causal Mediation Analysis
Author(s): Jeffrey M Albert* and Tanujit Dey and Youjun Li and Jiayang Sun and Wojbor Woyczynski and Rujia Liu and Meeyoung Min
Companies: Case Western Reserve University and Cleveland Clinic Foundation and Case Western Reserve University and Case Western Reserve University and Case Western Reserve University and Case Western Reserve University and Case Western Reserve University
Keywords: externalizing behavior; joint modeling; longitudinal data; mediation formula; potential outcomes; semiparametric regression

Limited work has been done on causal mediation analysis in the complex situation in which both the mediator and final outcome are measured repeatedly. Some recent approaches, including one using a continuous time model, are limited in being parametric and sensitive to model assumptions. To provide a more flexible and robust causal mediation analysis for longitudinal data, we propose a semiparametric continuous time model approach using a joint linear spline model for the mediator and the final outcome, when both are measured repeatedly. The component models use penalized splines, implemented in a mixed effect model framework, for both the mean and individual response functions. The joint model is fit in conjunction with an extended mediation formula and sequential ignorability assumption to estimate natural direct and indirect effects, both overall and as a function of time. The new method is applied to data from a cohort study to assess attention as a mediator of the effect of prenatal drug exposure on externalizing behavior in adolescence.

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

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