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dc.contributor.authorAbel, G
dc.contributor.authorElliott, MN
dc.date.accessioned2019-10-29T11:21:12Z
dc.date.issued2019-09-18
dc.description.abstractWhen the degree of variation between healthcare organisations or geographical regions is quantified, there is often a failure to account for the role of chance, which can lead to an overestimation of the true variation. Mixed-effects models account for the role of chance and estimate the true/underlying variation between organisations or regions. In this paper, we explore how a random intercept model can be applied to rate or proportion indicators and how to interpret the estimated variance parameter.en_GB
dc.description.sponsorshipPublic Health Englanden_GB
dc.identifier.citationPublished online 18 September 2019en_GB
dc.identifier.doi10.1136/bmjqs-2018-009165
dc.identifier.urihttp://hdl.handle.net/10871/39367
dc.language.isoenen_GB
dc.publisherBMJ Publishing Groupen_GB
dc.rights© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.en_GB
dc.titleIdentifying and quantifying variation between healthcare organisations and geographical regions: Using mixed-effects modelsen_GB
dc.typeArticleen_GB
dc.date.available2019-10-29T11:21:12Z
dc.identifier.issn2044-5415
dc.descriptionThis is the final version. Available on open access from BMJ Publishing Group via the DOI in this recorden_GB
dc.identifier.journalBMJ Quality and Safetyen_GB
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/en_GB
dcterms.dateAccepted2019-08-13
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2019-08-13
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2019-10-29T11:19:38Z
refterms.versionFCDVoR
refterms.dateFOA2019-10-29T11:21:16Z
refterms.panelAen_GB


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© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Except where otherwise noted, this item's licence is described as © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.