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Some thoughts on multi-parameter evidence synthesis

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If you have a question about this talk, please contact Li Su .

This will be a mixture of problems, remarks, argumentations, as well as stupid ideas, around the Bayesian modelling for multiple parameter evidence synthesis. In a general framework, evidence pieces from different sources are synthesized through a parametric synthesizer, which consists of a set of relationships between parameters built on our background knowledge. The talk will be focused on some fundamental properties of the synthesizer, such as model identifiability, parameter redundancy, evidence inconsistency, synthesis intensity, etc. The illustrative examples are taken from ordinary univariate or multivariate meta-analysis, mixed treatment comparisons, and generalised evidence synthesis.

This talk is part of the MRC Biostatistics Unit Seminars series.

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