Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial (Journal article)

Salanti, G./ Ades, A. E./ Ioannidis, J. P.

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dc.contributor.authorSalanti, G.en
dc.contributor.authorAdes, A. E.en
dc.contributor.authorIoannidis, J. P.en
dc.rightsDefault Licence-
dc.subject*Bayes Theoremen
dc.subjectClinical Trials as Topic/*statistics & numerical dataen
dc.subjectData Displayen
dc.subjectData Interpretation, Statisticalen
dc.subjectIschemic Attack, Transient/drug therapyen
dc.subject*Meta-Analysis as Topicen
dc.subjectModels, Statisticalen
dc.subjectPlatelet Aggregation Inhibitors/therapeutic useen
dc.subjectStroke/drug therapyen
dc.titleGraphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorialen
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Υγείας. Τμήμα Ιατρικήςel
heal.abstractOBJECTIVE: To present some simple graphical and quantitative ways to assist interpretation and improve presentation of results from multiple-treatment meta-analysis (MTM). STUDY DESIGN AND SETTING: We reanalyze a published network of trials comparing various antiplatelet interventions regarding the incidence of serious vascular events using Bayesian approaches for random effects MTM, and we explore the advantages and drawbacks of various traditional and new forms of quantitative displays and graphical presentations of results. RESULTS: We present the results under various forms, conventionally based on the mean of the distribution of the effect sizes; based on predictions; based on ranking probabilities; and finally, based on probabilities to be within an acceptable range from a reference. We show how to obtain and present results on ranking of all treatments and how to appraise the overall ranks. CONCLUSIONS: Bayesian methodology offers a multitude of ways to present results from MTM models, as it enables a natural and easy estimation of all measures based on probabilities, ranks, or predictions.en
heal.journalNameJ Clin Epidemiolen
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)

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