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Activity Number: 271
Type: Contributed
Date/Time: Monday, August 10, 2015 : 3:05 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #317749
Title: Joint Modeling of Outcomes from Studies with Clustered Reciprocal Control Designs
Author(s): Michael Pennell* and Abigail Shoben and Electra Paskett
Companies: The Ohio State University and The Ohio State University and The Ohio State University
Keywords: Bayesian Methodology ; Cluster Randomized Trial ; Community Intervention Study ; Generalized Linear Mixed Model ; Sample size determination ; Simulation Study
Abstract:

The Reciprocal Control Design (RCD) is an efficient way to run multiple intervention studies simultaneously. In the standard RCD, experimental units are randomized to one of m different arms with one arm serving as the intervention group for one study and the control for the other m-1 studies. The RCD is also an attractive design for community intervention studies requiring cluster randomization. Community intervention studies are costly and thus any design that allows sharing of resources across multiple studies would be appealing to investigators. In this presentation, we demonstrate that clustered RCDs also lend themselves to improved statistical efficiency through joint modeling of the study outcomes. Focusing on binary outcomes, we present results from simulation studies evaluating Bayesian joint models with subject-specific and cluster-specific random effects which are correlated across outcomes. Our simulations consider designs which share groups as well as designs which share subjects across studies. The models are also applied to data from two recent clustered RCDs. Implications of joint modeling on sample size determination for future studies is also discussed.


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

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