Please use this identifier to cite or link to this item: https://olympias.lib.uoi.gr/jspui/handle/123456789/20498
Full metadata record
DC FieldValueLanguage
dc.contributor.authorIoannidis, J. P.en
dc.date.accessioned2015-11-24T19:08:07Z-
dc.date.available2015-11-24T19:08:07Z-
dc.identifier.issn1531-5487-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/20498-
dc.rightsDefault Licence-
dc.subject*Clinical Trials as Topicen
dc.subject*Data Interpretation, Statisticalen
dc.subjectHumansen
dc.subjectLinkage Disequilibriumen
dc.subject*Models, Statisticalen
dc.subjectMolecular Epidemiologyen
dc.subject*Sensitivity and Specificityen
dc.titleWhy most discovered true associations are inflateden
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primary10.1097/EDE.0b013e31818131e7-
heal.identifier.secondaryhttp://www.ncbi.nlm.nih.gov/pubmed/18633328-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Υγείας. Τμήμα Ιατρικήςel
heal.publicationDate2008-
heal.abstractNewly discovered true (non-null) associations often have inflated effects compared with the true effect sizes. I discuss here the main reasons for this inflation. First, theoretical considerations prove that when true discovery is claimed based on crossing a threshold of statistical significance and the discovery study is underpowered, the observed effects are expected to be inflated. This has been demonstrated in various fields ranging from early stopped clinical trials to genome-wide associations. Second, flexible analyses coupled with selective reporting may inflate the published discovered effects. The vibration ratio (the ratio of the largest vs. smallest effect on the same association approached with different analytic choices) can be very large. Third, effects may be inflated at the stage of interpretation due to diverse conflicts of interest. Discovered effects are not always inflated, and under some circumstances may be deflated-for example, in the setting of late discovery of associations in sequentially accumulated overpowered evidence, in some types of misclassification from measurement error, and in conflicts causing reverse biases. Finally, I discuss potential approaches to this problem. These include being cautious about newly discovered effect sizes, considering some rational down-adjustment, using analytical methods that correct for the anticipated inflation, ignoring the magnitude of the effect (if not necessary), conducting large studies in the discovery phase, using strict protocols for analyses, pursuing complete and transparent reporting of all results, placing emphasis on replication, and being fair with interpretation of results.en
heal.journalNameEpidemiologyen
heal.journalTypepeer-reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά) - ΙΑΤ

Files in This Item:
There are no files associated with this item.


This item is licensed under a Creative Commons License Creative Commons