Please use this identifier to cite or link to this item: http://hdl.handle.net/11434/1864
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMcKenzie, Dean-
dc.contributor.authorThomas, Christopher-
dc.date.accessioned2020-04-27T00:15:03Z-
dc.date.available2020-04-27T00:15:03Z-
dc.date.issued2020-04-
dc.identifier.citationEur J Clin Invest. 2020 Apr 20:e13249en_US
dc.identifier.issn1365-2362en_US
dc.identifier.issn0014-2972en_US
dc.identifier.urihttp://hdl.handle.net/11434/1864-
dc.description.abstractAIM: Relative risks and odds ratios are widely reported in the medical literature, but the latter can be very difficult to understand. We sought to further clarify these important indices. METHODS: We defined both relative risks and odds ratios, then looked at the types of study for which each statistic is suited. We illustrated calculation of relative risks and odds ratios through analysis of tabled data from a recent published longitudinal study, using a 2x2 table, bar charts and R, the open source statistical programming language. Simple rules for when and how to use relative risks and odds ratios are presented. CONCLUSION: Understanding the difference between relative risks and odds ratios and when and how to use them may aid clinical interpretation, dissemination and translation of research findings.en_US
dc.publisherWileyen_US
dc.subjectClinical Researchen_US
dc.subjectClinical Interpretationen_US
dc.subjectHealth Promotion and Preventionen_US
dc.subjectCommunicationen_US
dc.subjectStatisticsen_US
dc.subjectRelative Risksen_US
dc.subjectOdds Ratiosen_US
dc.subjectResearch Methodsen_US
dc.subjectResearch Translationen_US
dc.subjectEpworth HealthCareen_US
dc.titleRelative risks and odds ratios: simple rules on when and how to use them.en_US
dc.typeJournal Articleen_US
dc.identifier.doi10.1111/eci.13249en_US
dc.identifier.journaltitleEuropean Journal of Clinical Investigationen_US
dc.description.pubmedurihttps://www.ncbi.nlm.nih.gov/pubmed/32311087en_US
dc.description.affiliatesDepartment of Statistics, Data Science and Epidemiology, Swinburne University of Technology, Melbourne, Australiaen_US
dc.type.contenttypeTexten_US
Appears in Collections:Pre-Clinical

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


Items in Epworth are protected by copyright, with all rights reserved, unless otherwise indicated.