title: [Bayesian statistics: what, how and why?].
abstract: Bayesian statistics is an alternative form of statistics that provides a way to systematically integrate new information with existing information. Bayesian methods are very suitable for evidence synthesis. Bayesian outcomes are easier to interpret than standard statistical outcomes. For instance, Bayesian methods allow for determining the probability that a difference in effect between two treatments will be clinically relevant. The use of Bayesian methods is becoming more prevalent.
authors.affiliation: Radboudumc, afd. Health Evidence, Nijmegen.
authors.forename: Willem H
authors.initials: WH
authors.lastname: Woertman
authors.forename: Hans M M
authors.initials: HM
authors.lastname: Groenewoud
authors.forename: Gert Jan
authors.initials: GJ
authors.lastname: van der Wilt
mesh_terms: D001499:Bayes Theorem; D003627:Data Interpretation, Statistical; D019317:Evidence-Based Medicine; D006801:Humans; D011336:Probability