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Web-based Bayesian Communication: the Bayesian z-test
Harold P Lehmann1, Alexander Barshay, L Allan Grimm
1Division of Health Sciences Informatics, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Abstract:
Bayesian Communication provides an explicit and quantitative way to combine a reader's preconceived notions with data from a study to help in making decisions, and thus implements the decision-analytic paradigm in the setting of interpreting and adapting research results. Article Assistant employs a three-tier architecture. The interface elicits users' prior belief and values; the article library provides data from the study, the system calculates the posterior belief distribution and sensitivity analysis on the fly, and provides an interpretation of the numerical results.
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