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.
Harold P Lehmann, Alexander Barshay, L Allan Grimm, Karen A Robinson, and Cynthia Sheffield.
Division of Health Sciences Informatics, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
AMIA Annu Symp Proc. 2005 Jan 1: 1023.
AbstractBayesian 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.