{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T02:26:04Z","timestamp":1740104764712,"version":"3.37.3"},"reference-count":25,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2015,2,1]],"date-time":"2015-02-01T00:00:00Z","timestamp":1422748800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2015,9,1]],"date-time":"2015-09-01T00:00:00Z","timestamp":1441065600000},"content-version":"tdm","delay-in-days":212,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","award":["MR\/L012286\/1"],"award-info":[{"award-number":["MR\/L012286\/1"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2015,4,15]]},"abstract":"<jats:p>When developing a new diagnostic test for a disease, there are often multiple candidate classifiers to choose from, and it is unclear if any will offer an improvement in performance compared with current technology. A two\u2010stage design can be used to select a promising classifier (if one exists) in stage one for definitive validation in stage two. However, estimating the true properties of the chosen classifier is complicated by the first stage selection rules. In particular, the usual maximum likelihood estimator (MLE) that combines data from both stages will be biased high. Consequently, confidence intervals and <jats:bold><jats:italic>p<\/jats:italic><\/jats:bold>\u2010values flowing from the MLE will also be incorrect. Building on the results of Pepe <jats:italic>et al<\/jats:italic>. (SIM <jats:bold>28<\/jats:bold>:762\u2013779), we derive the most efficient conditionally unbiased estimator and exact confidence intervals for a classifier's sensitivity in a two\u2010stage design with arbitrary selection rules; the condition being that the trial proceeds to the validation stage. We apply our estimation strategy to data from a recent family history screening tool validation study by Walter <jats:italic>et al<\/jats:italic>. (BJGP <jats:bold>63<\/jats:bold>:393\u2013400) and are able to identify and successfully adjust for bias in the tool's estimated sensitivity to detect those at higher risk of breast cancer. \u00a9 2015 The Authors. <jats:italic>Statistics in Medicine<\/jats:italic> published by John Wiley &amp; Sons Ltd.<\/jats:p>","DOI":"10.1002\/sim.6413","type":"journal-article","created":{"date-parts":[[2015,2,2]],"date-time":"2015-02-02T05:15:01Z","timestamp":1422854101000},"page":"1417-1437","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Correcting for bias in the selection and validation of informative diagnostic tests"],"prefix":"10.1002","volume":"34","author":[{"given":"David S.","family":"Robertson","sequence":"first","affiliation":[{"name":"MRC Biostatistics Unit, Institute of Public Health  Cambridge UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A. Toby","family":"Prevost","sequence":"additional","affiliation":[{"name":"King's College  London UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jack","family":"Bowden","sequence":"additional","affiliation":[{"name":"MRC Biostatistics Unit, Institute of Public Health  Cambridge UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2015,2]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1158\/1940-6207.CAPR-12-0501"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.7150\/jca.1.150"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/93.14.1054"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/93.5.334"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.3506"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4430"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.3863"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.1362"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/bimj.200410119"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/bimj.200810442"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1002\/bimj.201200245"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.5463"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/0167-7152(89)90133-8"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.2389"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1038\/415530a"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2008.07.031"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.5757"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.1080\/03610929208830831"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.3399\/bjgp13X668186"},{"key":"e_1_2_9_21_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/26.4.404"},{"key":"e_1_2_9_22_1","unstructured":"LeischF WeingesselA HornikK.bindata: Generation of artificial binary data 2012.http:\/\/CRAN.R-project.org\/package=bindata R package version 0.9\u201019."},{"key":"e_1_2_9_23_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.3837"},{"key":"e_1_2_9_24_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.5622"},{"key":"e_1_2_9_25_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btp460"},{"key":"e_1_2_9_26_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.1653"}],"container-title":["Statistics in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fsim.6413","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fsim.6413","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/sim.6413","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/sim.6413","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/sim.6413","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,5]],"date-time":"2023-10-05T13:00:56Z","timestamp":1696510856000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/sim.6413"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,2]]},"references-count":25,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2015,4,15]]}},"alternative-id":["10.1002\/sim.6413"],"URL":"https:\/\/doi.org\/10.1002\/sim.6413","archive":["Portico"],"relation":{},"ISSN":["0277-6715","1097-0258"],"issn-type":[{"type":"print","value":"0277-6715"},{"type":"electronic","value":"1097-0258"}],"subject":[],"published":{"date-parts":[[2015,2]]}}}