Bayesian Method of Borrowing Study-Level Historical Longitudinal Control Data for Mixed-Effects Models with Repeated Measures
Current historical borrowing methods focus on incorporating patient-level historical control information at only one time point. In this work, we propose a Bayesian hierarchical Mixed effect Models for Repeated Measures to incorporate aggregated study-level longitudinal historical control estimates into the concurrent trial that collected repeated longitudinal data.
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Meeting Highlights: DIA Innovating Clinical Trials in Europe: Unveiling the Future of Healthcare: EU-Funded Projects Transforming Real-World Evidence and Data Analytics
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New Drug Approvals in China Reached Record High in 2023
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Patient & Public Involvement – Stranded on the Adoption Curve?
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