{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T22:34:04Z","timestamp":1791326044406,"version":"4.3.1"},"reference-count":29,"publisher":"Wiley","issue":"21","license":[{"start":{"date-parts":[[2009,7,9]],"date-time":"2009-07-09T00:00:00Z","timestamp":1247097600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2009,7,9]],"date-time":"2009-07-09T00:00:00Z","timestamp":1247097600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"},{"start":{"date-parts":[[2009,7,9]],"date-time":"2009-07-09T00:00:00Z","timestamp":1247097600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"name":"NHS","award":["CSO ref: CZF\/1\/23"],"award-info":[{"award-number":["CSO ref: CZF\/1\/23"]}]},{"name":"Scottish Funding Council SINAPSE Initiative"}],"content-domain":{"domain":["wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2009,9,20]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Diagnostic tests are increasingly evaluated with systematic reviews and this has lead to the recent developments of statistical methods to analyse such data. The most commonly used method is the summary receiver operating characteristic (SROC) curve, which can be fitted with a non\u2010linear bivariate random\u2010effects model. This paper focuses on the practical problems of interpreting and presenting data from such analyses. First, many meta\u2010analyses may be underpowered to obtain reliable estimates of the SROC parameters. Second, the SROC model may be inappropriate. In these situations, a summary with two univariate meta\u2010analyses of the true and false positive rates (TPRs and FPRs) may be more appropriate. We characterize the type of problems that can occur in fitting these models and present an algorithm to guide the analyst of such studies, with illustrations from analyses of published data. A set of R functions, freely available to perform these analyses, can be downloaded from (<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/www.diagmeta.info\">www.diagmeta.info<\/jats:ext-link>). Copyright \u00a9 2009 John Wiley &amp; Sons, Ltd.<\/jats:p>","DOI":"10.1002\/sim.3631","type":"journal-article","created":{"date-parts":[[2009,7,10]],"date-time":"2009-07-10T02:49:46Z","timestamp":1247194186000},"page":"2653-2668","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":74,"title":["When are summary ROC curves appropriate for diagnostic meta\u2010analyses?"],"prefix":"10.1002","volume":"28","author":[{"given":"F. M.","family":"Chappell","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G. M.","family":"Raab","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J. 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