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Here, we develop a new estimation method for fitting models for network meta\u2010analysis with random inconsistency effects. This method is an extension of the procedure originally proposed by DerSimonian and Laird. Our methodology allows for inconsistency within the network. The proposed procedure is semi\u2010parametric, non\u2010iterative, fast and highly accessible to applied researchers. The methodology is found to perform satisfactorily in a simulation study provided that the sample size is large enough and the extent of the inconsistency is not very severe. We apply our approach to two real examples. \u00a9 2015 The Authors. <jats:italic>Statistics in Medicine<\/jats:italic> Published by John Wiley &amp; Sons Ltd.<\/jats:p>","DOI":"10.1002\/sim.6752","type":"journal-article","created":{"date-parts":[[2015,10,1]],"date-time":"2015-10-01T02:51:45Z","timestamp":1443667905000},"page":"819-839","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Extending DerSimonian and Laird's methodology to perform network meta\u2010analyses with random inconsistency effects"],"prefix":"10.1002","volume":"35","author":[{"given":"Dan","family":"Jackson","sequence":"first","affiliation":[{"name":"MRC Biostatistics Unit  Cambridge UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin","family":"Law","sequence":"additional","affiliation":[{"name":"MRC Biostatistics Unit  Cambridge UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jessica K.","family":"Barrett","sequence":"additional","affiliation":[{"name":"MRC Biostatistics Unit  Cambridge UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rebecca","family":"Turner","sequence":"additional","affiliation":[{"name":"MRC Biostatistics Unit  Cambridge UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julian P. 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