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Makambi","affiliation":[],"nameIdentifiers":[]},{"name":"Hyunuk Seung","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"A Non-Iterative Extension of the Multivariate Random Effects Meta-Analysis"}],"publisher":"Taylor \u0026 Francis","container":{},"publicationYear":2015,"subjects":[{"subject":"Cancer"},{"subject":"Mathematics"},{"subject":"FOS: Mathematics","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Mathematics","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Information and Computing Sciences"},{"subject":"Biological Sciences"},{"subject":"Microbiology"},{"subject":"FOS: Biological sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Biological sciences","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[],"dates":[{"date":"2015-01-02","dateType":"Created"},{"date":"2016-01-19","dateType":"Updated"},{"date":"2015","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1080/10543406.2014.919930","relatedIdentifierType":"DOI"},{"relationType":"IsPreviousVersionOf","relatedIdentifier":"10.6084/m9.figshare.1029354","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["127845 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"\u003ci\u003eMultivariate methods in meta-analysis are becoming popular and more accepted in biomedical research despite computational issues in some of the techniques. A number of approaches, both iterative and non-iterative have been proposed including the multivariate DerSimonian and Laird method by Jackson et al. (2010), which is non-iterative. In this study, we propose an extension of the method by Hartung and Makambi (2002) and Makambi (2001) to multivariate situations. A comparison of the bias and mean square error from a simulation study indicates that, in some circumstances, the proposed approach perform better than the multivariate DerSimonian-Laird approach. An example is presented to demonstrate the application of the proposed approach.\u003c/i\u003e","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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","url":"https://tandf.figshare.com/articles/dataset/A_Non_Iterative_Extension_of_the_Multivariate_Random_Effects_Meta_Analysis/1029354/1","contentUrl":null,"metadataVersion":3,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"viewsOverTime":[],"downloadCount":0,"downloadsOverTime":[],"referenceCount":0,"citationCount":0,"citationsOverTime":[],"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2016-01-19T01:17:03.000Z","registered":"2016-01-19T01:17:04.000Z","published":"2015","updated":"2020-09-04T23:08:41.000Z"},"relationships":{"client":{"data":{"id":"figshare.ars","type":"clients"}},"provider":{"data":{"id":"otjm","type":"providers"}},"media":{"data":{"id":"10.6084/m9.figshare.1029354.v1","type":"media"}},"references":{"data":[]},"citations":{"data":[]},"parts":{"data":[]},"partOf":{"data":[]},"versions":{"data":[]},"versionOf":{"data":[]}}}}