title: Web-based Bayesian Communication: the Bayesian z-test.
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.
authors.affiliation: Division of Health Sciences Informatics, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
authors.forename: Harold P
authors.initials: HP
authors.lastname: Lehmann
authors.forename: Alexander
authors.initials: A
authors.lastname: Barshay
authors.forename: L  Allan
authors.initials: L
authors.lastname: Grimm
authors.forename: Karen A
authors.initials: KA
authors.lastname: Robinson
authors.forename: Cynthia
authors.initials: C
authors.lastname: Sheffield
mesh_terms: D001499:Bayes Theorem; D002986:Clinical Trials as Topic; D003142:Communication; D003627:Data Interpretation, Statistical; D003661:Decision Support Techniques; D007257:Information Theory; D020407:Internet; D015233:Models, Statistical