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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