A Bayesian hierarchical framework for evidence synthesis for a single randomized controlled trial and observational data in small populations


The event is taking part on the Friday, Sep 28th 2018 at 11.00
Theme/s: BS
Location of Event: Alan Turing Room 306
This event is a: Public Seminar

Abstract: We consider the scenario of a single randomized controlled trial (RCT) comparing an experimental treatment to a control in a small patient population. In small populations the conduct of an RCT with a sufficient sample size might be extremely difficult or not feasible. Inspired by an ongoing paediatric study in Alport syndrome, we consider a study design in which information external to the randomized comparison, such as data arising from disease registries, are integrated into the design and analysis of an RCT in different ways. Based on the study design, statistical models for binary data are built. A Bayesian hierarchical framework is introduced for generalised evidence synthesis in order to estimate the quantities of interest. The performance of the proposed methods are evaluated under different scenarios by means of experiments.

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External Speakers

Dr Steffen Unkel